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THE RELATIVE IMPACI| OF MASS MEDIA
ON AMERICAN LIBERALISVI: 1945-1990

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THE RELATIVE IMPACT OF MASS MEDIA
ON AMERICAN LIBERALISM: 1945- 1990

By

Dave D’Alessio

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Communication

1996

ABSTRACT

THE RELATIVE IMPACT OF MASS MEDIA
ON AMERICAN LIBERALISM: 1945-1990

By

Dave D’Alessio

Based on a model holding that changes in public opinion are a
consequence of a multi-stage process in which interested groups, termed
“issue networks”, ﬁrst act to set the public’s agenda, then prime and
subsequently frame issues to the public through the media, the extensive
agenda-setting literature is reviewed. From it ﬁve basic expectations about
how public opinion changes were developed: That the media, and that policy
makers would have direct inﬂuence on public opinion; that the media
would also directly inﬂuence policy makers; that changes in liberal opinion
would lead in turn to increases in liberal activity; and that the exact form of
the model would differ on an issue-by—issue basis.

Public opinion data was supplied by the National Opinion Research
Center, while a sample of media opinion was drawn from the periodical
literature and content analyzed for statements overtly biased in a liberal of
conservative manner. Congressional and administrative actions were
gathered and coded, as were a variety of external socioeconomic factors.
Following data reduction, path models involving lagged variables of lags up
to eight years were developed based on correlational techniques. This was
done once for an aggregate model, and then twice more for single issue
models.

Results indicated that while the policy agenda directly inﬂuences

public opinion in all three models, the media’s impact in two of the three
models was indirect, action via its inﬂuence on the policy agenda. Changes
in public opinion did not appear to be connect with subsequent overt
behavior, but the single issue models indicated that the exact
interrelationship of media, public and policy varies from issue to issue. The
presence of a large number of even numbered lags suggests that public and
policy debate, and subsequent opinion change, is tied to congressional

election campaigning.

ACKNOWLEDGEMENTS

First, this research was possible in part to the assistance of the
undergraduate and graduate students who did the content analysis: Eric
Peltier, 'D'acey Birkenhauer, Chris Atwater, Lisa Noel, Kim Niemiec,
Kathleen Starman, Romy Barrett, Sheryl Wnek,Paula Johnson, and
especially Tim Rick of Michigan State; Patty Doran of Calvin College; and
Cindy Pancurak, Matt Spicer, Elizabeth Goodwin, Lydia J avins and Holly
Kingsley of Stockton College.

Second, Dr. Tom Smith of the National Opinion Research Center
graciously supplied all of the public opinion data for the cost of
photocopying. This study reﬂects the inspiration of much of Dr. Smith’s
research as well.

Third, as with every dissertation, this could not be possible without
the advice and support supplied by the committee: Jim Dearing (Chair),
Chuck Atkin, Frank Boster, and Todd Simon.

Fourth, as also with every dissertation, no dissertation would ever be
possible without the support of the people who believed I could do this even
when I wasn’t sure myself: Drs. Mike Allen and Nancy Burrell of the
University of Wisconsin - Milwaukee, Dr. Paul Mineo of the University of
Connecticut - Hartford, and Mr. and Mrs. John J. D’Alessio of Glen Head,
N .Y.

iv

TABLE OF CONTENTS

LIST OF TABLES vii

LIST OF FIGURES x

CHAPTER ONE

LITERATURE REVIEW AND EXPECTATIONS
Agenda Setting Studies
Priming and Framing
Media and Public Opinion
Other Agenda-Opinion Relationships
Theoretical Background
Access to Media
Issue Networks and Social Structures
Operationalization
Liberal Issues and Liberal 'h'ends
Liberalism
Bias in the Media
Potential Drawbacks in the Use of Public Opinion Data
Expectations

8&SEEBEEEGEKAH

CHAPTER TWO
MEASUREMENT AND ANALYSIS
Measurement of Public Opinion
Determining the Media Agenda
Measuring the Policy Agenda
Socioeconomic Factors
Method of Analysis

BEBEEE

CHAPTER THREE
RESULTS
Public Agenda
Media Agenda
Policy Agenda

§sss

External Socioeconomic Factors

Path Analysis - Overall Model

Impact on Output Variables
Sub—Analysis: Foreign Affairs

Univariate Analysis

Path Analysis - Foreign Affairs Model
Sub-Analysis: Race and Ethnicity

Univariate Analysis

Path Analysis: Race and Ethnicity Model

Comparison of Path Models
Overall Findings

CHAPTER FOUR
DISCUSSION

Public Opinion Change
Causation

Basic Findings
Collaborative Inﬂuence
External Socioeconomic Factors
Role of Nation’s Media
Media Bias
Communication Generally
Caveats

Theoretical Considerations
Power

Concluding Note

165
165
167
168
169
172
175
177

186
188

LISTOFTABLI‘B

Table 1 — Measurement of the Factors of Liberalism

Table 2 - Gross Changes in Public Agenda and Number of Active
Trends by Year and Content Area

Table 3 - Topic Headings Used in Reader’s Guide

Table 4 - Mean Media Bias by Year and Content Area

Table 5 - Congressional Activity by Year and Content Area

Table 6 - Administration Agenda by Year and Content Area

Table 7 - Socioeconomic Inputs by Year and Input Area

Table 8 - Socioeconomic Outputs by Year and Content Area

Table 9 - Overall Analysis Matrix of Correlations for Public Opinion
by Content Area

Table 10 - Overall Analysis Autocorrelations and Partial
Autocorrelations Public Opinion

Table 11 — Intercoder Reliabilities on Media Agenda by Content Area

Table 12 - Overall Analysis Matrix of Correlations for Media Agenda
by Content Area

Table 13 - Overall Analysis Autocorrelations and Partial
Autocorrelations Media Agenda

Table 14 - Overall Analysis Matrix of Correlations for Congressional
Agenda by Content Area

Table 15 - Overall Analysis Matrix of Correlations for Administration
Agenda by Content Area

Table 16 - Overall Analysis Autocorrelations and Partial
Autocorrelations Congressional Agenda

Table 17 - Overall Analysis Autocorrelations and Partial
Autocorrelations Administration Agenda

Table 18 - Overall Analysis Matrix of Correlations for Socioeconomic
Inputs by Area

Table 19 - Overall Analysis Autocorrelations and Partial
Autocorrelations Socioeconomic Inputs - Economy

Table 20 - Overall Analysis Autocorrelations and Partial
Autocorrelations Socioeconomic Inputs - Propinquity

Table 21 - Overall Analysis Matrix of Correlations for Socioeconomic
Outputs by Area

Table 22 - Overall Analysis Autocorrelations and Partial
Autocorrelations Socioeconomic Outputs

28 EB 88? EB §§38833383 83

101

Tables (cont’d)

Table 23 — Overall Analysis Lagged Correlations with Public Opinion

Table 24 - Overall Analysis Original Matrix of Correlations for
Lagged Predictors

Table 25 - Overall Analysis Matrix of Corrected Correlations for
Lagged Predictors

Table 26 - Overall Analysis Matrix of Reconstructed Correlations

Table 27 — Overall Analysis Matrix of Residuals

Table 28 - Overall Analysis: Output Model Lagged Correlations
with Socioeconomic Outputs

Table 29 — Overall Analysis: Output Model Matrix of Correlations
for Lagged Predictors

Table 30 - Overall Analysis: Output Model Matrix of
Reconstructed Correlations

Table 31 — Overall Analysis: Output Model Matrix of Residuals

Table 32 — Sub-Analysis: Foreign Affairs Autocorrelations and
Partial Autocorrelations Public Opinion

Table 33 - Sub-Analysis: Foreign Affairs Autocorrelations and
Partial Autocorrelations Media Agenda

Table 34 — Sub-Analysis: Foreign Affairs Autocorrelations and
Partial Autocorrelations Administration Agenda

Table 35 — Sub-Analysis: Foreign Affairs Autocorrelations and
Partial Autocorrelations Congressional Agenda

Table 36 - Sub-Analysis: Foreign Affairs Lagged Correlations
with Public Opinion

Table 37 - Sub-Analysis: Foreign Affairs Matrix of Correlations
for Lagged Predictors

Table 38 - Sub-Analysis: Foreign Affairs Matrix of Reconstructed
Correlations

Table 39 — Sub-Analysis: Foreign Affairs Matrix of Residuals

Table 40 - Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Public Opinion

Table 41 - Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Media Agenda

Table 42 — Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Administration Agenda

Table 43 - Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Congressional Agenda

Table 44 — Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Socioeconomic Inputs:
Occupational Segregation by Race

Table 45 - Sub-Analysis: Race and Ethnicity Autocorrelations and
Partial Autocorrelations Socioeconomic Outputs:
Election of Black Congressmen

Table 46 — Sub-Analysis: Race and Ethnicity Lagged Correlations
with Public Opinion

viii

EEEEQQEEEQEEEEE

EE

147
148

151

152

Tables (cont’d)

Table 47 — Sub-Analysis: Race and Ethnicity Matrix of Correlations
for Lagged Predictors

Table 48 - Sub-Analysis: Race and Ethnicity Matrix of
Reconstructed Correlations

Table 49 - Sub-Analysis: Race and Ethnicity Matrix of Residuals

Table 50 - Residual Matrix Comparison of Path Models

ix

156

15)
161

LISI‘ OF FIGURES

Figure 1 - McCombs’ Four Part Typology of Agenda Setting Studies

Figure 2 - The Interrelationship of Media, Policy, and Public
Agendas, and Socioeconomic Factors

Figure 3 — Net 'h‘ends in Liberalism in the United States, 1945-1990

Figure 4 - Year-by-Year Changes in Net Liberalism, 1945-1990

Figure 5 -- Liberal Trends Demonstrating a “Liberal Plateau”

Figure 6 — Liberal Trends Demonstrating a Perturbed Linear Trend

Figure 7 — Operational Deﬁnition Overall Model

Figure 8 - Cumulative Annual 'h‘end, 1940-1994

Figure 9 -— Average Net Trend, 1940-1994

Figure 10 — Overall Analysis - Final Path Model

Figure 11 — Overall Analysis: Output Model Final Path Model

Figure 12 - Foreign Affairs Sub-Analysis Final Path Model

Figure 13 — Race and Ethnicity Sub-Analysis Final Path Model

Figure 14 — Frequency Distribution of Net Liberal-Conservative
Statements per Article

ﬁééﬁssacasse q

53
H

Chapter One
Literature Review and Expectations

The history of the study of mass communication effects in the US. is
largely a history of a search for impacts on individuals. Whether conducted
in the ﬁeld or in the laboratory, the emphasis is typically on change in the
individual subjects; error terms are generally assumed to be made up of the
individual differences between the participants.

The advantages of research about individuals are many. Small subject
pools are readily available, manipulations can be made as strong as
necessary (or allowable; Hovland, 1959), experiments or ﬁeld studies can be
constructed in ways which permit strong claims of internal and/or external
validity (Campbell and Stanley, 1966), and thus results can be obtained
which permit strong causal claims (Hume, 1748/1955). Research techniques
appropriate to the study of individuals are widely taught and statistical
procedures can be straightforward. Moreover, the micro-level focus on
individuals reﬂects the widespread concern in democratic societies of undue
inﬂuence on individuals and their rights. ~

However, the emphasis on media effects on the individual may be
inappropriate, or at least too restrictive. For instance, the notion of the
media as a social force, above and beyond being literally a "medium" or
“mirror” (conveyer of a speciﬁc story, for example, the Kennedy
assassination, Greenberg and Parker, 1965; or type of content such as
violence, Milavsky, et al., 1982), with an important role to play in the

governing and administration of a nation, is common in academic

1

2

disciplines such as political science (Linsky, 1986), sociology (Lang and
Lang, 1968), and journalism (White, 1962, 1965). Communication, often
studied through these diverse perspectives, may be especially appropriate to
broad, as opposed to restrictive, emphases.

One might also argue that to emphasize impacts on the individual is
inherently reductionist, with the pitfalls and problems associated with the
use of reductionist rather than holistic (or "systems") approaches. Von
Bertalanffy (1968) points out that reductionist “covering law” approaches
fail to permit higher order, complex interactions, and that the necessity of
experimental control requires examination of closed systems; Monge (1973)
draws the distinction between systems models, which recognize patterns in
behavior, and “covering law” models, which impose patterns on behavior;
together, these ideas suggest the possibility of destroying the phenomenon
under observation by the act of observing it.

Another problem unique to the study of mass communication and
mass societies is the problem of effect sizes: If a television program were to
be created of such power and impact that it would speciﬁcally and
unquestionably cause 2,500 of its 25,000,000 viewers to run amok in the
streets, scientists would be forced to tease from amongst the gamut of
individual differences the very small effect size of .0001. 'II‘eated, however,
at the level of the society, 2,500 rioters would create a substantial and
discernible impact on the crime statistics of that historical epoch.

Finally, there remains the recently abused notion of "mass" media.
It is possible for commercially viable media to exist with audiences of only
hundreds; it is unquestionably the fashion, for sound economic reasons, for
media sources to engage in "narrowcasting", or the search for smaller but

demographically and attitudinally more closely deﬁned audiences for

3

which premium rates can be charged (DeFleur and Dennis, 1988). But the
media institutions whose "power" is the subject of discussion and debate,
protest and pr0posed legislation, receive that "power" directly from the fact
that they reach millions of citizens quickly and efﬁciently, with content over
which mass media decision-makers exert editorial control.

Approaches to mass media as a monolithic social structure (i.e. “the
media” in the same sense as “the government” or “the courts”) have been
few, and, for the most part, limited to theoretical positions whose empirical
testability is obscured by the broadness of the scope of the position
(McLuhan, 1964; Meyrowitz, 1985). Within American culture, for instance,
television signals reach working television sets in 98% of households
(Biitner, 1985); and many of the 2% who would form a comparison group
are so different from the majority in so many other ways as to make
conclusions drawn from comparison problematic. Studies on the Innuit
(Canadian Eskimos) do not generalize well to the US. population at large.

One area where mass communication research has started to move
in the direction of considering the media as one social structure (that is, as
a coherent body with needs and desires which manifest themselves in the
functioning of the society) and the people as a second social structure has
been the area of agenda setting research. While many of the studies
continue in the reductionist vein, the vast accumulation of public opinion
research has permitted the examination of the populace's response as a
whole, within the limits of sampling error. And that same accumulation
permits analysis of trends, directions, and changes in public opinion, some
of which may be explicable in terms of the dynamics of the populace, and
some of which may be explicable in terms of the impacts of other structures

in the society, including the educational process, the decisions of

4

government, and the media, on that populace.

AgendaSetﬁngStudies

Iyengar and colleagues (Behr and Iyengar, 1985; Iyengar and
Kinder, 1987; Iyengar and Simon, 1993) increasingly conceptualize public
opinion change as a multi-step process in which mediated messages
increase the salience of issues (agenda setting), then communicate
evaluative frameworks (priming), as well as the “evidence” on which
evaluation is based (framing). This suggests that Opinion changes created
by media consumption is a multi-stage, contingent process1 whose overall
eﬂiciency is limited by the efficiencies of the separate, intervening processes
(Kenny, 1979). Each of the various stages has been the subject of some
degree of empirical research.

Agenda setting as a demonstrable communications phenomenon is
generally traced to Maxwell McCombs’ and Donald Shaw's (1972) classic
correlation (r=.967) between the number of news articles on a set of issues
and the public's ranking of those issues in terms of importance during the
1968 election campaign. Since then, the ability of the media to set the
public's agenda (that is, as Bernard Cohen, 1963, paraphrased "(The Press)
is stunningly successful in telling its readers what to think about. ") has
been demonstrated in a number of ways under a variety of conditions.

Recent reviews (Weaver, 1984; Rogers and Dearing, 1988) leave little
doubt of the generalizability of the McCombs and Shaw data, at least at the

 

' In short, the process can being conceptualized as being analogous to a grade school
math class: the students are told what problem to solve (agenda setting), given the
appropriate equation (priming). and told what numbers to put into the equation (framing).
The result is an opinion.

5

level of aggregate data. Studies using individuals rather than publics as
the objects of study (consider Erbring, Goldenberg, and Miller, 1980; Watt
and van den Berg, 1981) show substantially smaller effect sizes, but are still
able to demonstrate agenda setting effects, at least for the short term (Watt
and van den Berg) or on certain topics (Erbring, et al.).

Funkhouser (1973) was among the ﬁrst to take advantage of the vast
body of data represented by the Gallup polls and media content indexes. He
discovered a Spearman's rank order correlation of .78 between the number
of articles about a given topic and its selection as the "most important
problem facing the nation" by Gallup respondents for the entire decade of
the 1960's. This correlation suggests a strong relationship but not
necessarily agenda setting per se, however, since the time ordering of
content vs. opinion was not established. This is of import in that the
relation discovered also can be construed as evidence of the so-called
"mirror" hypothesis, that the media simply reﬂect the wants, desires, and
attitudes of its consuming public (Bogart, 1969).

In response, a wide variety of studies have attempted to not only
demonstrate a causal priority of media over public opinion, but additionally,
attempted to determine the length of time needed for the impact to occur.
Watt and van den Berg (1981) were able to predict the number of resident
complaints received by the Federal Aviation Administration concerning
Concorde overﬂights using, among other factors, the amount and net
"direction" of media coverage of the problem on the previous day. (The
impact of media on this question was negligible six months after onset -
people had learned to cope with the noise.) Stone and McCombs (1981)
isolated impact lags of from two to six months for new topics to impinge on

the public consciousness. Eaton (1989), with access to biweekly data, found

6

that for many subjects the largest impacts were immediate, but that several
(fear of war, criticism of the government) showed lags of 4 to 10 weeks.

This, combined with Shaw and McCombs' original ﬁnding that the
largest correlations between media and public Opinion occurred when ALL
media sources, and not just those known to be used by the subjects in
question, were taken into account, suggests that media content has to
"build up", or hold interest long enough to penetrate the sheer density of
media content surrounding each member of the public (obviously, the
Concorde noise issue failed to build up sufficiently to show long term
impact).

Both McCombs (1982) and Weaver (1984) have attempted to lay some
sort of structure onto the numerous agenda setting studies conducted
during the '70's and early '80's by proliferating McCombs' four part
classiﬁcation scheme through the literature. This classiﬁcation scheme
holds that the literature can be organized as a two by two array, shown as
Figure 1, with the relevant dimensions being level of data (individual vs.
group) and type of dependent measure (single measure or unrelated set vs.
interlocked set). Weaver points out that studies using aggregate data (Types
1, interlocked, and III, single measure) show substantially larger agenda
setting eﬁ'ects than those based on individual data; and that the studies of
Type II (Individual data on an interlocked set of measures) show the
weakest effects of all.

The study proposed herein will be of Type III, using group data on a
single issue. This will permit the advantages of using aggregate data (as
outlined above) without requiring the mathematical complexity of an
interlocked set of dependent measures.

The ability of the media to set the public’ 3 agenda has also been

Level of Data
Group Individual

Interlocked Type I Type II
Type of
Dependent
Measure

Single measure Type III Type IV
From McCombs (1982).

Figure 1
McCombs’ Four Part Typology of Agenda Setting Studies

8

demonstrated experimentally by Iyengar and Kinder (1987). Iyengar and
Kinder presented audiences with taped newscasts edited to either contain
stories on topics under study, or else substitute,“control” stories. While
their method of reporting their results is problematic,2 Iyengar and Kinder
demonstrate agenda setting effects consistently across 14 studies, covering
a wide variety of topics, and involving a total of 1151 participants. Iyengar
and Kinder also used two-stage least squares in a separate analysis to
demonstrate a contemporaneous impact of television news on the public’s
selection of a “most important problem” in public opinion polls.

Rogers and Dearing (1988) traced the development of agenda setting
and tied the communications school tradition of examining the impact of
the media on public opinion to the political science tradition of considering
the interrelationship of media and policy makers (such as government
ofﬁcials). They in turn produced the integrated model reproduced as
Figure 2, and also the terminology "media agenda", "public agenda", and
"policy agenda", which are operationalized respectively as media content
proportions, public opinion, and governmental action.

This model is of consequence for two reasons. First, it integrates both
research traditions and suggests hypotheses about the inﬂuential nature of
the components. Second, it provides a mechanism for the intervention of
the "real world”, permitting the possibility of measuring and controlling
potential spurious variables and therefore correction of spurious

relationships. However, it also raises the question of whether these

 

’ In particular, Iyengar and Kinder are somewhat cavalier with the common practice
of indicating statistically signiﬁcant results with an asterisk. They regularly star items
with p<.20, and on one table have starred p<.60! However, their results are significant (by
any standard) far more frequently than is explicable by chance, and non-significant
results are consistently in the predicted direction, suggesting that the use of cumulative
analysis techniques (Hunter, Schmidt, and Jackson; 1982) would support their claims.

 

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The Interrelationship of Media, Policy and Pub-
lic Agendas, and Socioeconomic Factors

Source: Rogers and Dearing (1988)

10

research traditions are related apart from the identity of the dependent
variable, Of the interrelationship Of the various agendas.

Rogers, Dearing, and Chang (1991) attempted to provide a full test Of
all aspects Of the Rogers and Dearing model for the issue of Acquired
ImmunO-Deﬁciency Syndrome (AIDS), as well as adding agendas for two
other elite groups, scientists and public opinion pollsters. Unfortunately,
the analytic method chosen, time series analysis by the ARIMA method
(Box and Jenkins, 1976) permitted neither the ability to test competing
causes nor the ability to include public Opinion (which, due to the irregular
periods between tests, did not form a regular time series).

Given these caveats, Rogers, Dearing and Chang were able to discern
four different periods in the life Of this developing story. In the ﬁrst, the
media agenda is driven by the science agenda and the number of AIDS
cases reported (it is worth noting that the media agenda in turn drives the
reporting Of AIDS cases and not the actual number Of cases). During the
second era, the media inﬂuence the pollsters while in the third era there is
reciprocal feedback between media and pollsters; and ﬁnally the media and
the scientists drive policy makers to action. It can easily be seen how much
could be gained by the inclusion Of public Opinion in this analysis. (The
public agenda was stated to have been driven by the media agenda as a
result Of the inspection Of a plot Of number of stories and public Opinion
against time.)

Subsequently, Trumbo (1995) extended Rogers, Dearing, and Chang's
techniques to include both a measurement of the public’s agenda (which he
termed “extreme concern index” or E01) and path analysis, and applied
them to the topic Of global warming. Using a semi-monthly time frame,

Trumbo showed a complex interrelationship between the media and policy

11

agendas -- news papers and the science press inﬂuence policy, which later
inﬂuences television content, which itself inﬂuences policy about two
months later. Both television content and the policy agenda affect the public
agenda, the former within the same semi-monthly time period and the
latter ﬁve months subsequently.

Of interest in Trumbo’s results is that the policy agenda’s impact on
the public agenda is negative in sign. This is inconsistent with the
literature generally, although the length Of the lag suggests that process
resulting in this effect may differ from that present in the short-term
studies which make up most of the body Of the literature. (The
interrelationship, positive in sign, which 'humbo discovers between the
policy and media agendas indicates that in the short-term -- one month or
less -- there will be a measurable, but spurious, positive relationship

between the policy agenda and the public agenda.)

Priming and Framing

Priming and framing have a much shorter history in the
examination Of media effects. Extending the works Of Herbert Simon (1979),
Iyengar and Kinder (1979) posited the existence Of priming effects created by
news casts and provided substantial experimental evidence in support of
that effect across topics including energy, defense, inﬂation, civil rights,
and so on (vide Iyengar and Kinder, 1979, pp. 65-70). Similarly, Krosnick
and Brannon (1993) showed that media coverage of the Gulf war inﬂuenced
the manner in which survey respondents evaluated the Presidential
performance Of George Bush.

Subsequently, Iyengar ( 1991) published the results Of his extensive
studies into the ability Of the media to frame issues. He found framing

12

eﬂ'ects in experimental settings which covered a plethora Of content areas,
including crime, poverty, racial inequity, and terrorism. Further, Iyengar
and Simon (1993) found evidence of both framing and priming effects in
their analysis Of public Opinion data from the Gulf war time period.

Pan and Kosicki (1996) seem to have bridged the gap between issue
framing by the media and subsequent changes in public Opinion on the
topic Of race. Although hypothesized impacts expected to be evoked by “non-
information-oriented” media failed to be detected, the use Of information-
oriented media by white survey respondents is associated with the belief
that the condition Of blacks is due to “not trying hard enough” (frame) and
the subsequent rejection of Afﬁrmative Action and spending programs

(Opinion).

Outside the parameters Of the agenda setting/priming/framing
approach, there have been a variety Of longitudinal studies Of the impact Of
media, or, as Martin (1976) would point out, the impact Of the
"informational role" Of the media. These studies share the general
characteristic Of assuming the media are simply carriers Of "real-world"
information tO the public, despite the knowledge that the media can, do, and
must discriminate from among many stories (c.f. White, 1950; Bagdikian,
1971; Berkowitz, 1990).

The most common Of these studies consider the dynamics Of
presidential popularity, as a wide variety of pollsters have attempted to
gauge the public's evaluation Of a sitting president (Hibbs, 1982; Brody and
Page, 1975; Mueller, 1970; MacKuen, 1983); indeed, the Gallup organization
has measured the President’s popularity on a monthly basis (with the

13

exception of election months, for fear Of potentially creating a bandwagon
, effect) since the Truman administration, presenting a 43-year time series of
data.

Most Of these studies ﬁnd a general decline in presidential popularity
over time, which Mueller attributes to the alienation Of various minority
groups across time. Economic factors such as inﬂation and unemployment
also have predictive power, and it is diﬁicult to attribute these effects to the
media per se; while the populace might have learned of these economic
phenomena through the media, the fact remains that they are a part of the
make-up of individual life -- increased bills at the checkout line, for
instance, or the diﬁculties Of cousin Charlene in locating a job.

Two other, salient, points emerge from this group of studies. One is
that the media (or mediated information) do impact the public's Opinion of
the president's performance (although not necessarily in a predictable way,
as Brody and Page, 1975, point out). The second is that there appears to be
two classes Of mediated event: Common, everyday news; and major,
dramatic events which Mueller describes as having a “rally-around-the-
ﬂag” effect and which MacKuen describes as showing “presidential
authority”. The impact Of the former class of event on the public dissipates
relatively rapidly (on the order of several months -- see below) while the
impact of the "rally" events is large and relatively permanent; MacKuen
hold that such events "(touch citizens) in a new way, changing their
fundamental view Of each president's character (pg. 184)." In other word,
these major events create actual opinion change. (A mechanism for this
will be suggested below.)

Sufficient evidence exists to suggest that these ﬁndings are
generalizable tO a degree. In Davis' (1952) seminal study of media on belief

14

change, the amount Of coverage accorded violent crime impacted beliefs
about how frequently violent crimes occurred more strongly than the actual
crime rate (although it should be noted that this ﬁnding was not as strong,
or even was reversed, for other forms of crime). More or less
simultaneously Davies (1952) isolated short-term reactions in public Opinion
to economic and foreign affairs news that were fairly consistent across
social and economic class; unfortunately, he did not consider longer term
impacts.

Again within the short term, Page, Shapiro, and Dempsey (1987)
were able to isolate media impacts on a variety of public policy preferences
covering "many different kinds Of foreign and defense (n=32) and domestic
(n=48) policies (pg. 26)". By restricting their study to short term effects (to
merit inclusion, policy time series had to cover no more than three months
between data points), Page, et al., (1987 ) uncovered impacts due to
statements of the Opposition party, interest groups, media commentary,
experts, and the courts; the largest effect was due to media commentary,
while that created by interest groups and the courts was actually negative!

Mueller (1979) used news content (in this case, the belligerent
posturings Of the US. and the USSR.) to predict the public's perceptions
Of the likelihood Of the outbreak Of the next world war. The magnitude Of
impact was strictly time ordered: belligerence within the last 10 days
predicted public perceptions more strongly than news coverage across the
previous four months, which in turn impacted public perceptions more
strongly than news coverage across the previous year, although all time
periods contributed (statistically) signiﬁcantly to the model.

Finally, Smith (1987) attempted an ambitious study of mutual

causation between public Opinion on a variety Of topics (seven in all,

15

including crime, the economy, health care and public recreation) and
newspaper mentions of those issues. He discovered that newspaper
coverage led public opinion on economic development issues whereas public
concern about the environment led newspaper coverage; however, problems
with the use of Ordinary Least Squares techniques on autoregressive data
(speciﬁcally, that the assumption Of uncorrelated error terms is violated;
see Cook, Dintzer, and Mark, 1980) render Smith's ﬁnding problematic.

As a summation of these studies, it is reasonable to state that media
content can inﬂuence public opinion strongly in the short term and weakly
in the long term. Data from the presidential evaluation studies suggests
that the information creating long term impact is the vivid”, dramatic news
while the impact of the day-tO-day content is transitory. Exogenous (that is,
external) variables such as economic factors can also have impact, and,
indeed, can have larger impact than information. And, ﬁnally, Smith's
(1987) study suggests that public opinion has the potential to impact media
coverage along with possible media impact on the public. The
consequences Of these ﬁndings for the proposed study will be discussed
below.

Other agendaopinion relationships

The media agenda is expected to affect not only the public agenda but
also the policy agenda (Rogers and Dearing, 1988); additionally, the public
agenda should inﬂuence the policy agenda (which is the function of
classical democracy); and the policy agenda and the media agenda should

demonstrate reciprocal impacts.

 

'Although not necessarily vivid in terms Of media depiction. As Iyengar and Kinder
(1987) discovered, the public appears willing to “blame the victim” if possible, regardless of
the TV production techniques used to communicate the person’s plight.

16

There is almost certainly an impact Of the public agenda on the
media, speciﬁcally, an economic impact. Because the mass media are
proﬁt-making organizations dependent to some degree on mass audiences,
and because it has been demonstrated that people will outright reject
information which is too divergent from their existing viewpoints (see for
instance Hovland, 1959), a pressure is created which forces the media to
respond to audience preference, which are, by deﬁnition, middle of the
road. Gitlin (1980), for instance, points out that the media regularly engage
in the trivialization of extremist groups as a result of the media's
essentially conservative (in the sense Of "supporting the status quo" rather
than "supporting the right wing") nature. However, this “consumer
feedback” is generally small, slow to take effect, and difficult to discern;
gatekeepers simply keep their perceptions of the desires of their audience in
the back Of their mind as they select material, so the resulting content is
generally close to the audience’s values.

In a theoretically perfect democracy, the impact Of the public agenda
on the policy agenda should be absolute: the majority should rule. In the
U.S., however, only the legislative branch, the chief executive, and lower
levels of the judiciary are directly accessible to the voter, and then only at
speciﬁed time intervals. As we have seen, however, the public's evaluation
of the president occurs continuously and not just once every four years.
Thus, while in theory the policy agenda is perfectly and immediately
responsive to the public agenda and in practice the executive (as the creator
of the policy agenda) is responsive only in quadrennial cycles, the reality is
somewhere in between -- policymakers are neither perfectly responsive nor
perfectly unresponsive within an election term.

Erikson (1976), going back to Gallup data from 1936-1937, discovered

17

strong relationships (point biserial correlations of .97, .64, .63, and .17)
between public Opinion and legislative action on capital punishment, the
proposed child labor law constitutional amendment, and the use of female
jurors. Although a correlation is not proof Of causality, the mechanism for
voters inﬂuencing policy (by voting) is stronger and surer than the reverse,
leading to the conclusion that public opinion had some impact on policy for
these issues.

Similarly, Page and Shapiro (1983) were able to ﬁnd reasonably
substantial impacts Of public Opinion on public policy on a wide variety of
issues, including taxation, military action, and trade. They discovered that
during the 1935-1979 epoch, on 231 issues in which public Opinion made a
substantial change, public policy made a congruent change 43% Of the time,
remained unchanged 33%, and made a non-congruent change only 22% Of
the time (during the ﬁnal 2% of cases a change whose impact was
indeterminable was made); in other words, public Opinion preceded policy
change in over 3/4 Of cases, these alterations leading to a congruent change
almost four times in nine.

Finally, Gaziano (1978) showed that there was a relationship between
public Opinion and voting on the Supreme Court on First Amendment cases
during the late '30s through the 19608, ﬁnding that the Court was more
likely to uphold free speech rights for radical groups when public Opinion
poll results favoring such rights were at or above 40%, and, especially,
when public support was rising. While the Supreme Court is appointed for
life (and, ergo, not subject to being turned out Of Ofﬁce by irate constituents),
as physical members Of the Washington establishment justices are subject
to lobbying and other forms of public pressure.

That the media agenda affects the policy agenda also seems well

18

established, although by fewer ﬁeld studies and a greater degree of
anecdotal data. Linsky (1986) reports that 96% Of government Oﬂicials
stated that the media impacted federal policy (whether this is a case of the
“third person” effect —"Yes, it sure impacts those other people even though
it doesn't matter to me" — has yet to be seen).

Cohen (1983) points out that although policymakers desire to some
degree to be responsive to public opinion, they prefer idiosyncratic sources,
such as an intuitive “feel” for the needs of voters, and including contacts
with the media, to Objective reporting Of mass Opinion by polling
organizations. In this sense the media function as an elite subsector of the
public-at-large.

Cook, Tyler, Goetz, Gordon, Protess, Leff, and Molotch (1983)
conducted a ﬁeld study examining the impact Of television news reports
(about ﬁ'aud and abuse in the health care/nursing home industry) on the
public, on interest group elites, and on local government policy elites (i.e.
government Oﬂicials with responsibilities concerned with health care and
the elderly). The government policy elites exposed to the reports perceived
signiﬁcantly (statistical) more fraud and abuse in the health care industry,
were more likely to believe that the public perceived the same, and were
more likely to see the need for government action, than those who were not.
(There was also a signiﬁcant impact on the public, although not on the
interest group elites, whose Opinion can be summarized with the phrases
"We knew that already" and "There are other issues involved as well".) In
their follow-up, Cook, et al., (1983) point out that the call for legislation on
the health care fraud issue made by the Senate Permanent Investigations
Subcommittee was the result of an interaction between the government

policy makers and journalists directly, sidestepping the Opinions Of the

19

public (Cook, et al., 1983). .

The inﬂuence of policy makers on the media is less well studied and
based to a greater degree on anecdotal data, although Wanta and Foote
(1994) recently demonstrated that the President, at least, has the ability to
inﬂuence the media’s agenda in topic areas on which he is either an
important source or has a personal interest. Wanta and Foote accomplished
this by using time series analysis of Presidential statements recorded in the
ﬂeekGCnmnilatinnnfEmidentialermentsas a predictor ofTV news
content as recorded in the Vanderbilt Amhiygs News Abstracts. Signiﬁcant
effects were found for both positive and negative lags, indicating that the
President inﬂuences media coverage and that stories in the media
inﬂuenced Presidential statements, respectively.

More typical of the examinations of the impact Of policy makers on
the media is that of Linsky (1986), who points out that relations between
press and president were extremely close at the founding of the republic:
both Thomas Jefferson and Alexander Hamilton started newspapers and
among Andrew Jackson’s closest advisors were three newspaper editors.

Contrariwise, according to Linsky, modern press-government
relations are built on the principle that the press and government have an
adversarial relationship. Gitlin (1980) reports instances of Lyndon Johnson
calling editors Of national newspapers and magazines to discuss (loudly
and obscenely) the interrelationship Of their reportage and his
administration. Thompson (1973) documents Richard Nixon's disdain for,
and attempted manipulations of, the national reporters covering his 1972
reelection campaign, and also points out the dependency Of reporters on
government ﬁgures using the Eagleton affair as an example. Several

reporters, most noticeably Donaldson (1987), remarked on Ronald Reagan's

Z)

willingness to inﬂuence the media agenda by the use of pseudo-news
"exclusive" reports to individual members of the media.

Weaver and Elliott (1985) extend this by examining the
interrelationship between activity of the Bloomington, IN, City Council and
local press reports Of that activity. While they were able to demonstrate a
distinct gatekeeping effect by the press (238 of 405 total agenda items were
eventually reported), they also found that items pertaining to the local
economy (and its development — of course an issue of primary concern at
the local level) were reported almost entirely and exactly as desired by the
council. Weaver and Elliott attributed this to the necessity Of relying on the
council members as information sources on those issues; thus, the
government policy makers were able to transform the media agenda to
their favor.

Rogers and Dearing (1988) suggested that while public Opinion
impacts policy, the reverse is probably not true. Little published data
appeared to treat this issue, although a mechanism by which this reverse
link could Operate can be envisioned. As Schlesinger (1939) had pointed out
that policy in the US. tends to run in conservative/liberal cycles lasting on
the order Of 14-16 years. These cycles tend to push the country in an overall
liberal direction due to their nature: during liberal cycles legislation is
passed which is ignored rather than repealed during conservative cycles.
Thus, at the advent of a new liberal cycle, the new generation sees the
previous liberal policy position as "the law Of the land", and the new liberal
position pushes toward the left from there.‘

 

‘ Although in excess of 50 years Old, this work reasonably predicted rightward turns in
the 1948 and 1978 eras as well as a liberal trend circa 1963. 'l\vo further comments follow:
the next liberal swing should occur shortly (ca. 1993); and the Reagan administration may
have interrupted this process by its wholesale program of deregulation during the early
1980's.

21

Subsequently Sharp (1992) analyzed the impact Of administration and
congressional policy on the public agenda and found that it was possible
that Presidents Nixon, Carter, Reagan and Bush had been able to inﬂuence
the salience Of the drug war to the public by their activities. In particular,
she shows that President Nixon was able to mobilize public opinion in favor
Of his policy of providing methadone to heroin addicts by creating fears of a
heroin addiction epidemic. Similarly, a steady increase in congressional
hearings on drugs starting in 1981 was followed by an upturn in the
percentage of maple naming drugs as the most important problem facing
the nation in 1985.

Whackgmund

Blumer (1946, 1964), via Price (1992), views public Opinion formation
as a coalescence process: people identify a problem, interest groups form
around it and propose a series of solutions to the problem, the proposals are
debated, and policymakers execute one or more Of the solutions and then
evaluate the results (see also Foote and Hart, 1953). The stages Of the
process (and progress through them) is driven by a variety of social
processes, the most important of which are communication - which allows
interested parties to mobilize social groups and individuals to their causes
— and legislation.

Within this process, many writers divide the citizenry into two main
groups, the public, which is engaged in the issue, and the mass, which is
not.“ It is clear that the composition of the public varies to an extent on an

issue-by-issue basis (with a set Of major exceptions which will be discussed

 

‘ Lippmann adds a third, the spectator, which observes the debate but does not enter into
it.

below.)

When one considers the consequence of this at the level Of an issue of
national consequence, it becomes clear is that - via communication
through a wide variety Of media — members of the public come together into
ad hoc groupings, formal or informal, characterized by some common
stand on the issue in question. The stand may be in favor of or Opposed to
any or all Of the proposed solutions to the problem; it may also be devoted to
raising or lowering the national salience of the problem itself. We will call
this ad hoc grouping an “issue networ ”.°

Thus, the formation Of an issue is attendant with the formation Of a
minimum Of two (pro and con) issue networks, and generally a
substantially larger number. It seems likely that issue networks arise
originally via interpersonal communication channels. Klapper (1960),
Thibault and Kelley ( 1959) and others have remarked on the relative
homogeneity of opinion within sociological groups. Within the group would
develop, via interpersonal channels, common perceptions of the salience of
an issue and the appropriate stand to take on the issue.

Regardless of the stand, the salience Of the issue needs to be
sufﬁciently high to motivate the group to action toward implementing social
policy consistent with the stand. A leader or set Of leaders who were unable
to persuade members Of their sociological groups of the importance Of an
issue or the validity Of a solution would probably not be able to cause an

issue network to coalesce. But the motivating force for the group can be

 

'The term issue network was chosen in order to avoid the pejorative connotations of the
term "special interest group", which may be the most Obvious synonym. Formally deﬁned,
we can describe an issue network as a set of interconnected people who share a perception of
the salience of an issue and a stance on that issue. The network generally has a formal
structure which includes only a small number of the members, created as members elect
each other to ofﬁces, award each other titles, and, when money is available, pay salaries to
some of the officers.

23

stated simply as "power": the development of sufﬁcient political force to be
able to impose the group's solution on the problem. As Baumgartner and
Jones (1993) point out, this usually takes the form of attempting to achieve a
“policy monopoly”, which would yield to the network the opportunity to
establish policy in the absence of effective Opposition.

National inﬂuence, however, requires some form of national access,
and it is impossible in this day and age to form a functioning issue network
on an issue of national concern without access to some form of mass
mediated communication’, especially bearing in mind the wide variety of
such channels available, including news reports (free but uncontrolled by
the source), advertisements (under source control but expensive), letters to
the editor (free but with no guarantee of publication), and so on.

Gaining access to mass media of various kinds moves the issue
network from an interpersonal unit to a mediated unit. This in turn
requires an organizational structure designed to communicate with the
members of the network and to communicate for the network, including a
(frequently professional) hierarchy and leadership, and a means of
identiﬁcation for the members (frequently ID cards are issued by issue
networks; see Appendix A). As this membership broadens and becomes
more diffuse, the pursuit Of power as a goal is joined by the perceived desire
for prestige and money, since these will attract members and facilitate the

 

7 Note that in the issue network it is not necessary for the members to share social space
or perception, even though the original group from which the issue network evolved may
have.

application of power.’3

The media serve the function Of enabling the social identiﬁcation Of
their consumers (Price, 1992). Members Of the mass come to identify with,
and frame issues in the terms of mediated models with which they are
presented.

The ultimate target Of the various issue networks is not the public
(which, being composed Of members Of issue networks, has already taken
sides), but the mass. It is within the mass that the money lies, and within
the mass that the votes lie. So public debate on an issue can be considered as
the attempt to frame the issue for the mass audience in the terms of the
position advocated by the advocating issue network.“

For our purposes, we will describe framing as the implantation into
the minds Of an audience Of an image which is evoked with the evocation Of
an issue. Entman (1993) points out that the ﬁmctions of a ﬂame is to deﬁne
problems, diagnose causes, make moral judgments and suggest remedies;
so, a well-selected frame causes the mass audience to associate the moral

judgments and/or suggested remedies Of the framing issue network with

 

'This was very recently - 6 November 1996 - articulated by Libertarian Party
Presidential candidate Harry Browne (1996) in a press release to the party (and educators
interested in political communication).

“...Although we can experiment with short-cuts, the only sure way to [communicate our
message] is through the steady building of party membership, which will lead to the money
necessary to attract attention, which will lead to the media coverage that will make us part
of the national discussion.”

Browne’s release, which was distributed electronically, is available as Appendix B.

'This is consistent with Baumgartner and Jones’ (1993) contention that political
entrepreneurs attempt to inﬂuence policy by means of imposing their own deﬁnition on an
issue. Clearly this refers to a framing process.

%

the issue at hand.” In short, agenda setting via framing can be not only a
process affecting salience but also one which effects attitudinal responses.

Thus, leadership in the issue network can be seen to require a
minimum of two roles (although it is possible for the same person or set Of
people to occupy both roles): there must be someone to conceptualize the
frame appropriate to the network, and someone to articulate it to the public.
This can be seen quite clearly in the arena of marketing issues, where an
agency may be speciﬁcally hired to do the conceptual work, and the agency
may in turn specify a particular spokesperson.’L1

This framing takes place largely through the media12 (as the most
convenient means of reaching the mass audience), and is another of
functions Of communication within the process. The media convey
messages from the various issue networks to the audience. (While member
units of the media...consortia Of journalists or newspapers...may also
participate in the debate and either be members of issue networks or form
their own, the message conveyed is no different than that of any other issue

network. The media may serve as source, but they do serve as channel.)

Access to Media
Issue networks can gain access to national media via a number of

mechanisms. They can, of course, buy media time if their ﬁnancial

‘° Entman's definition of framing -- "'lb frame is to select some aspects of a perceived
reality and make them more salient in a communication text, in such a way as to promote
problem deﬁnition, causal interpretation, moral evaluation, and/or treatment
recommendation (pg. 52)" -- is not inconsistent with ours but lacks the persuasive element
implied by deﬁning framing as a process designed to create an association between image
and issue.

" This thinking was in part elucidated by the Libertarian Party's Presidential
nominating convention, July 4-6, 1996. In the Libertarian Party, the conceptual role is
played in large part by founder David Nolan, who is alive and very much on the scene. The
public articulation role is left to the Presidential nominee, however.

" At this point, this theory overlaps that of Iyengar.

%

resources are sufﬁcient (and their cause “mainstream” enough), or they
can gain media access by staging “pseudoevents” and inviting media
coverage. Each of these is problematic: ads are poorly attended (Bechtel,
Achelpohl, and Akers, 1972), and the media event supplies the opportunity
for the media to reframe issues in their own terms (c.f. Gitlin, 1980). Issue
networks can also gain media access by recruiting or developing members
of suﬁcient prominence as to be “newsworthy”. (The latter is typiﬁed by, for
instance, the establishment Of “think tanks” who provide “experts” to
comment on news events; c.f. Cooper and Soley, 1990.)

Next, we arrive at a notion of mass Opinion. The mass can be
conceived as the playing ﬁeld on which the issue networks vie for
supremacy, again, because it is with the mass that the human resource
(new members), the ﬁnancial resource (donations, taxes and fees), and the
political resource (votes) reside. (Although Fan, 1988, holds that mass
opinion can be accurately reproduced by sophisticated content analysis of
media messages, it is the mass, not the media, which possesses the
numbers Of people and the ﬁnancial resources.)

Issue networks play their game by attempting to publicly frame the
issue in their own terms”, generally in the terms most suited to the
national media which act as their channels, i.e. the sound bite, PSA, and
infomercial. The issue networks which have the ability to exert greatest
inﬂuence on the process are those which exert the greatest inﬂuence on

policy making bodies (via recruitment, ﬁnancial inducement, or perception

 

"A good example which is otherwise outside the scope of this paper is the abortion issue,
debate on which revolves implicitly, although rarely explicitly, around the point at which
human life arises. By claiming to be "Pro (human) Life" and by declaring abortion to be
murder, it is clear that one side frames the debate in terms of human life starting at the
point of conception. Pro-choice advocates have been heard to use the phrase "Potential
human life" to describe the fetus, clearly implying that "human" life commences at some
point after conception.

27

Of the ability to deliver votes) and those with greatest access to the national
media, typically those with direct access to the media because they are
members of the media (i.e. in this case serving in their role as source as
well as channel).

The simple act of framing an issue, Of course, is not necessarily
suﬂicient to causing changes in public opinion; instead, some mechanism
must exist which permits this process. Both Zaller (1992) and Iyengar (1991)
suggest (or imply) such mechanisms, Zaller taking an approach which is
derived from, and expands on, Anderson's (1974) Information Aggregation
model, and Iyengar essentially a cultivation-based approach.

Zaller modiﬁes the Information Aggregation model using issue
involvement; speciﬁcally, he feel that a highly involved person seeks out
more messages and is more selective in receiving consonant information
than a less involved person. Hence, a highly involved person in a mixed
message environment differentially seeks out large numbers of consonant
messages, thereby (via aggregation) developing a more extreme Opinion
(i.e., becomes "polarized"). A less involved person seeks fewer messages
and does so less selectively, and thus is more likely to be "mainstreamed" to
the prevailing position created by the net ﬂow Of messages. (It should be
noted that the competition between polarization and mainstreaming
suggests a way of operationally distinguishing between the public and the
mass. Further, given that Zaller conceptualizes involvement as continuous
rather than dichotomous, he does not make the public/mass distinction
common elsewhere.)

Iyengar does not speciﬁcally refer to the media effects he examines
as occurring via a cultivation process, but it is clear that he is stipulating

that sort of mechanism. Tapper's (1995) recent reconstruction Of cultivation

$

(in order to account for otherwise anomalous research results) states that
mediated messages are ﬁltered by consumers via a variety Of processes,
including selectivity, chronic affective state, and motives for viewing.

Whether cultivation or integration based, each approach has the
capability to explain mass media effects as we know them, which can be
quickly summarized with the catchphrase “the less you know, the greater
the effect.” In cultivation, information-based psychological defenses (e.g.
selectivity) go into effect with the attempt to move (or change) closely held
attitudes; these defenses act to resist movement and/or to restore a shifted
attitude to its previous location. On the other hand, weakly held attitudes
not well integrated into the cognitive structure and not held close to the
belief “core” are shifted (and shiftable) to a much greater degree. In
information integration theories, beliefs build an informational “mass” as
messages accumulate, reducing the impact of subsequent messages.

In both cases, when considering the audience member who is not
strongly involved, message repetition plays a large role in impact.
Additionally, it seems reasonable that a message's ability to stand out as
dramatic or attention getting (in radio terms, to "punch") maximizes its
effectiveness by maximizing its likelihood of being consumed rather than
ignored. An effective frame, almost by deﬁnition, is dramatic and attracts
attention because Of its innate ability to evoke powerful imagery; and it is
more likely that a dramatic, evocative image than a mundane image will be
repeated simply because of its dramatic nature (Patterson, 1993, points out
the concern of the media with "the new, the unusual, and the sensational;”
pg. 37). Hence, an eﬂ'ective frame is by its nature better able to impact the
members Of the mass via either the mechanism proposed by Zaller or that Of

Iyengar.

Q

This model of cognitive structure also explains the distinction
between the short-term impacts of everyday media information as opposed
to the long-term effect of the "rally" event. The everyday information
impinges only on the outer, regions of the attitude “sphere”; a single
attitude is perturbed brieﬂy and then the holder’s psychological defenses
cause him or her to draw in new information which draws the perturbed
attitude back to its "proper" location. But "rally" events, as pointed out
above, penetrate to the central core Of the belief structure and perturb it,
which in turn causes a reconﬁguration Of the attitude structure around it.
Since responses to Opinion questionnaires are derived in part from this
attitude structure, the person in question will evince attitude change.

Please note that "rally" events are by their nature large, compelling,
and dramatic; also note that this large, compelling, and dramatic nature in
turn impacts the media coverage they receive. While they may not
speciﬁcally engender or communicate a new frame, they are covered more
thoroughly, with greater amounts Of both visual material and also
analytical material than the mundane story that disappears after a day or
two on the ﬁont page. This gives greater opportunity for access to the
underlying belief structure, and, under either paradigm, leads to greater

Opinion change.

Issue Networks and Social Structures

Congress is a particularly interesting entity when considering the
impact Of the issue network on public opinion, as it should be Obvious that
the Congress is not a monolithic entity but instead can be considered a

microcosm of the nation in that issue networks arise within it and debate

ED

publicly on the nature Of a solution.14 Unlike the mass, however, Congress
is a small and relatively homogeneous body which by its deﬁnition is
expected to be engaged in many problems and by its nature is responsive to
the types Of inducements offered by an issue network. In short, while
inﬂuence on Congress by issue networks is similar to that on the mass
audience, it proceeds more quickly, and in ways which are more
immediately Obvious. Recruitment of members Of Congress by an issue
network greatly assists the network's attempt to ﬂame an issue, as the
Congress members can use their access to the media to further transmit
the frame.

This can happen in an Administration or on the Supreme Court as
well; in fact, the existence of issue networks on the Court has been
formalized in the form Of the issuing Of dissenting opinions. But the
relatively small size of the Court (and the general delay required for it to
exercise its powers), and the relative homogeneity Of thought within an
Administration (which, ultimately, answers to the President) make the
activity of the issue network less Obvious.

It is worth noting, however, that issue networks can appear, or even
be started, in an Administration: Wanta and Foote (1994) show that a
President is able to inﬂuence the media’s agenda on issues “on which he
has a pet interest” (pg. 437), and Sharp (1992) discusses the impact Of
President Nixon’s interest in the drug problem on the public’s perception of

 

“This is consistent with Lippmann's (1914/1962) classiﬁcation of Congress into
"routineers" and "inventors." (Note the analogy to "actors" and "spectators".) One can
easily point to Senators who were clearly members of, or leaders of, an issue network
throughout history: Taft on labor in the '40's, Kefauver on organized crime in the '50's,
Hatﬁeld on the Vietnam War in the '60's, Moynahan on welfare and social reform in the
'70's, Nunn on defense in the '90's. But these are clearly exceptions to the standard model
of a senator, and it is worth noting that none of them is associated with leadership in
another issue network.

31

drugs as an important problem.

It would seem that the issue network system remains fairly stable
across time. Apart from the organizational beneﬁts of the status quo
(money, power, and prestige, as discussed above), the fact Of the competing
issue network structure suggests that no win is either absolute or
permanent. Ins become outs and outs ins, but the networks are in the game
for the long run.

In addition, to extend the sport metaphor, it is reasonable to assume
that an issue network prefers not to be defeated, and thus is frequently
willing to redeﬁning its framing to avoid ﬁnal defeat, in the same manner
that strategies shift in team sports under the threat of loss. And defeat need
not be permanent nor entail the end of the issue network, as the same
people may still pursue the same end while using a different network
structure.”

Similarly, in an effort to maintain the level of relevance necessary to
retain money, prestige, and power, issue networks can also reframe issues
in order to designate them as relevant to the issue network.” '

This is reasoning consistent with Baumgartner and Jones’ (1993)
contention that there are no equilibria in American politics. As they deﬁne
the goal Of issue networks (which they call “political entrepreneurs”) as the
development of a policy monopoly favoring themselves; a monopoly by
deﬁnition requires that only one side prevail. Presuming rationality, each
side strives to gain the “win” side of the “win-lose” dichotomy, and will act

in such a way as to avoid the “lose” side.

 

“As the Christian Coalition grew out of the Moral Majority, or the Reform Party from
United We Stand.

"Again drawing from the Libertarian convention, Libertarians deﬁne the issues of
gun control, abortion, and gay marriage as civil liberties issues of the type central to
libertarian philosophy (and in fact have similar positions on each of them).

Opsrationalization

For the purpose Of examining the impact of the issue network on the
framing of public Opinion, measurement problems arise immediately.
Activities of the issue network’s members who are also members of key
social bodies, i.e. policy makers and the media, are a matter of public
record. Congress, for instance, is speciﬁcally mandated by the Constitution
to keep a journal Of its activities, and does so, in the form of the
Congressional Record. More importantly, as decisionmakers, the actions Of
Congress are considered inherently newsworthy. Similarly, the content-
based articles in the periodical literature and major newspapers, and even
the evening network news are extensively archived and indexed.

But the activities of issue networks outside this social structure are at
best — at best — incompletely recorded. Rallies, direct mail campaigns,
infomercial and PSA play...all these vary by market and are rarely recorded
or indexed; they are in essence only partially recoverable data. Thus, the
only places where the issue network's impact can be measured are in the
policy and media agendas.

At the gross level, then, this again suggests a conceptual model
resembling that presented by Rogers and Dearing (1988) and presented in
Figure 2. The addition Of external socioeconomic factors, especially the
input factors, is based on the assumption that the issues and grievances
which engender issue networks have an Objective component, i.e. if there
was no unemployment, there would be no unemployment “problem” around
which an issue network could coalesce (note that the ﬁrst step of the process
involves identifying the problem; Blumer, 1964). Similarly, as noted above,
the prime function Of the issue network is the accumulation and

deployment Of political power, the application of which should be

33

demonstrated in subsequent events.

Liberal Issues and Liberal Trends

Apart from the purely pragmatic question Of the existence of a large
body Of already prepared data on the issue, the construct “liberalism”,
which overarches a wide variety of speciﬁc beliefs and Opinions (Smith,
1990), is of import in two manners.

'Ib return to the nature Of the governing of the United States, it is
worth reiterating that many policy actions are in principle based on the
notion Of vox populi, vox dei .17 Plainly, if the people speak with a liberal or
conservative voice, a consequence Of this speech will exist in the law of the
land, speciﬁcally, in the shape Of the law of the land.

As Vedlitz (1988) points out, that shape is at least partly determined
by the underlying tenets Of ideology. He identiﬁes several beliefs basic to
conservative political thought, including that the free market is the best
progenitor of social and economic development, that the cultural of the
United States is essentially a meritocracy, and that federal programs and
regulation are at best ineffective and at times outright harmful. Similarly,
Smith (1990) isolated liberal beliefs, including preferences for federal
regulation and intervention, reform, civil libertarianism, and
multinationalism, among others. The consequences Of an electorate
choosing a conservative viewpoint espousing, for instance, decreased
government regulation and taxation against a liberal one preferring the
use of regulation and tax monies as a support to civil liberties are Obvious.
The question then follows: 'Ib what extent is this underlying popular belief

set manipulated and manipulable? For the extent of manipulation

 

-_'-’The voice of the people is the voice of God.

34

represents control of the nation by elite groups of whatever political ﬂavor.

Liberalism

The question of liberalism possesses academic import as well in its
role as one of the overarching constructs Of American public Opinion in that
its action (or lack thereof) constitutes evidence supporting or disconﬁrming
entire classiﬁcations of theories of social change. Appelbaum (1970)
classiﬁed theories Of social change into a four part taxonomy: evolutionary
theories, equilibrium theories, conﬂict theories and “rise and fall” or cyclic
theories. Although differing in details, these various classiﬁcations make
predictions about the trend in liberalism in the United States: an
evolutionary theory would predict a drift on one direction or the other; a
change in the direction of the drift, from liberal to conservative or vice
versa, is not predicted by evolutionary theories and thus suggests that they
lack validity.

Despite recent electoral results and the discussion revolving around
the development Of a vocal religious right in the United States, the best
Objective evidence is that the nation is substantially more liberal than it was
during the 19503. Thornton, Alwin, and Camburn (1983), for instance,
were able to use data from an 18 year panel study Of mothers and daughters
to show a growing attitude towards more egalitarian gender roles in
homemaking not just for the daughters (born 1962) but for the mothers as
well.

Mueller (1988) points out that the nation has grown more tolerant of
"leftists", i.e. Communists, Socialists, the Russians in general, and so on,
based on his analysis of General Social Survey (GSS) data gathered between
1940 and 1985 on items such as "Should a Communist teacher he ﬁred?"

35

(the proportion stating "Yes" decreasing from 89% in 1954 to 51% in 1985).
In a similar manner Page and Shapiro (1982) were able to track the policy
preferences Of Americans, ﬁnding, for instance, that Americans preferred
more civil liberties, greater availability of birth control information, and
expanded civil rights in the 1970s than they did in the 19308, 19408, and
19508.

Unquestionably the most thorough of the studies based on public
Opinion data, however, is that Of Smith (1990), which is based on 455 time
series collected between 1945 and 1987 which can reasonably be related to an
over-arching construct Of "liberalism" subdivided into 17 subcategories
(such as civil liberties, labor, foreign aﬁ‘airs, and sex; see Smith, 19903)
possessing at least face validity (this was derived using a content-analytic
approach to published data; the formal deﬁnitional structure appears in
Chapter Two). Smith analyzed the 455 time series using Taylor's (1980)
hierarchical approach (to determine which of (a) constant, (b) linear and (c)
non-linear trends best ﬁts the data, proceeding in that order, so if the
assumption of constancy is not rejected, further tests are not performed),
and then used the signed average of all trends across all items to produce
the data presented graphically in Figure 3. (Although Smith provides
points pre-1945, he warns that they are "inadequate"; thus, they have not
been reproduced herein.)

As can be seen in Figure 3, public Opinion in the US was trending in
the conservative direction (as indicated by the signed average less than 0.00)
until 1959. As an example, in 1949, for every 1% rise in in a liberally
trending item, there was a 1.53% rise in a conservatively trending item,
yielding a signed average of -0.53% (liberalism having arbitrarily assigned
to the positive end of the axis). Since 1959, public Opinion has trended in the

 

 

 

 

 

u L PM L + L A 4
121 L
1.
3.
5.
E 41
3 at L
e
I I
.21 P
I >
.1. ,
5' '
- , - . ..... , - . - , 1 1 L 1 1
Yﬂl'
Figure 3

Net trends in Liberalism in the United States, 1945-1990
Source: Smith (1990)

liberal direction at varying rates.

Figure 4 shows the year-by-year changes in the overall curve, or what
might be termed the "acceleration". As can be seen, public Opinion has
been accelerating in the liberal direction since 1952-3, with only a brief
conservative acceleration from 1974-1977.

This leads to the question Of whether this construction is "real", or
simply an artifact Of the measurement process. Smith concedes that the
average conservatively trending single item gains responses about 1.31
percentage points more conservative yearly, while the average liberal item
gains 1.32 points annually; the total liberal gain is due to the preponderance
Of the number of liberal trends versus conservative trends.

In one sense the veridicality Of the liberal trend is unprovable. It is
impossible to determine whether a given set of new items conceived of by
Gallup or Roper researchers is random or biased toward one end of the
spectrum or the other. But at the moment of conception it is not known in
what direction the item will trend; it is not until later that it develops that
two-thirds Of the trends are towards the liberal end. Further, trends on at
least two Of the subcategories are conservative (crime and social welfare)
while others are essentially constant (spending and taxes, labor); one would
expect a consistent methodological bias to impact these subcategories as
well.

It is not impossible to conceive of an inconsistent methodological bias
- for instance, demand effects on the part Of the polls takers might account
for the results — but it seems more likely that the polls are measuring a true
change in public Opinion which has indeed been reﬂected in American
society. To run the risk Of using instance conﬁrmation, a recent

controversy was raised in west Michigan aroun 1992 about a public

 

 

 

 

 

 

Figure 4
Year-By-Year Changes in Net liberalism, 1945-1990
Source: Derived from Smith (1990)

$

appearance to be made by former Freedom Rider James Meredith, then a
staff member to North Carolina Senator Jesse Helms. Consider these
differences versus 1955: In 1955, there are no former Freedom Riders, and
there are certainly no black men on the staﬂ's of conservative southern
senators. In fact, as White (1966) points out, a conservative southemer
senator such as Helms would have been a member of the Democratic rather
than the Republican party.

A second viewpoint (Sullivan, Piereson, and Marcus, 1979) holds that
such demonstrated increases in liberalism, and particularly intolerance
for leftist groups (for instance, see Nunn, Crockett, and Williams, 1978), is
an artifact of the measurement on a set of consistent items across time; that
while the pollsters continue to ask about the same groups over time,
Americans ﬁnd new groups against which to demonstrate intolerance.
They go on to demonstrate that when faced with a menu of extremist
groups (including not only communists and socialists, but also the Klu
Klux Klan, the John Birch Society, and the Symbionese Liberation Army),
the public shows substantial abhorrence; thus the argument follows that
Americans are as intolerant as ever, but that the same Old intolerance is
directed toward a different set Of groups. Mueller (1988) has demonstrated
several methodological ﬂaws with Sullivan, et al.'s, (1979) work, one Of
which, the inclusion of a "no Opinion" category in more recent data,
provides the capability of simultaneously demonstrating both increased
tolerance and intolerance, as both ﬁgures have declined since the 19508,
when no such "middle ground" response category was accepted.

Also related to the question of the veridicality of an increase in
liberalism over the last four and a half decades could be Iyengar and
Kinder’s (1987) priming effect. Although Iyengar and Kinder apply

40

priming to the evaluation Of presidential popularity, the notion of changing
the standards against which activity is judged (priming) could apply
equally well to judgments Of political appropriateness as well as political
performance. That is, an Observed increase in the performance of liberal
activities might occur not because the nation was becoming more self-
consciously liberal, but because these activities are no longer perceived as
liberal.

In one sense this is a distinction without a difference. If the
behaviors advocated by classic liberal thought (the basis of Smith’s content
analysis) are performed and the positions advocated by classic liberal
thought are supported, the result is the same whether these actions and
positions are identiﬁed as liberal or not! Providing a test Of the role of
priming in the process, i.e. whether the Observed changes are a priming
eﬁ'ect or not, would be fairly straightforward; participants would be
presented with a menu of activities and positions, and asked to identify
which of them were liberal. Substantial deviation from the positions and
actions advocated by classic liberal thought would be evidence Of priming.

Assuming the validity Of Smith's increase in liberalism, another
question about the trend curve in Figure 3 is what it has to say about trends
in the same items in the recent past, i.e. 1987-1990. Smith (1990) claims that
the overall curve demonstrates what he terms a liberal plateau, or a
decrease in the acceleration toward liberalism. This interpretation is
demonstrated graphically in Figure 5; Smith also selects four items from
his set that clearly show this effect.

It is not unreasonable, however, to interpret the same data as a
perturbed linear trend, illustrated as Figure 6 (actually, a very gentle curve
with a large perturbation ﬁts slightly better than a straight line). The

Nam

41

 

 

the; E

A
v

 

A

in.» 12--

P

 

 

wi-

 

- v ‘ v ‘ v j V f f '1 v t v t v ' v ' V

Figure 5
Liberal 'ITends Demonstrating a “liberal Plateau”

 

New
IDNh-bt

 

 

 

 

p
- V r VVTr ' r v I ‘ v ' v ' T ' I ' v v

Figure 6
Liberal Ttends Demonstrating a Perturbed Linear Trend

43

distinction between trends will be Of consequence in the prediction of the
causes of the liberal trend in public Opinion, as it is the locations of points of
inﬂection which make possible stronger predictions from exogenous data;
data expected to come on-line from the 1987-1993 polls in a few months
(Smith, 1991) should enable the accurate selection of one Of those two
models.

A ﬁnal question is whether these changes in liberalism can be
simply explained as either artifacts in the shift Of the demographic
composition Of the nation or are simply the result of exogenous causes
outside the scope of the study (for instance, if all the variance in liberalism
can be explained by changes in the education level of the nation, there is
little reason to consider the role Of mass media in the process).

Prima facie (“ﬁrst face”) arguments Oppose this possibility; in
general, the constituency of the nation has been aging since the 19508 and
conventional rhetoric holds that the older audience is generally more
conservative. Exter and Barber (1986) demonstrated that while older cohorts
have grown more conservative in such areas as attitudes about capital
punishment and pornography, they have moved toward the left on
government spending, civil rights, and education; indeed, the Oldest cohort
Of their study was substantially more liberal than the 30-40 year Old (baby
boomer) cohort. Danigelis and Cutler's (1991) basic conclusion was that
period effects inﬂuence the Older and younger cohorts in similar ways, and
that age is an inadequate measure Of essential conservativism (and, by
analogy, liberalism); Holsti and Rosenau (1980) showed that occupational
status was a fair better predictor of conservatism than age (or, more
precisely, historical epoch Of young adulthood, their division of the
constituency being based on where the respondent's young adult years stood

44

with regard to World War H, the Korean War, the between-war years, and
the Vietnam conﬂict).

Davis (1975) provided a thorough analysis of the public Opinion data
demonstrating a increase in tolerance in America, and concluded that 5
percent of the change in tolerance can be attributed to age cohort to which
participants belonged, 4 percent to educational advancement between age
cohorts, and 13 percent to increasing tolerance that crosses age cohort and
educational group boundaries, i.e. for the purposes of this proposed study,
constitutes a true liberal shift.

Following Smith’s (1990) summary, Davis (1992) returned to the
demographic analysis of the liberal shift. Although be located conservative
shifts within cohorts for the late 1970’s followed by a 1980’s rebound, he felt
that the shift itself was created by cohort replacement. Thus, it can be
accepted that the United States has grown more liberal since the 19508.

Such demographic analyses leave open the “why?” question. That
Older age cohorts should be more conservative is suggested by information
aggregation theories (Anderson, 1974): Older people have received more
messages and thus have greater inertia to overcome. Why more recent
cohorts should be more liberal than the cohorts they replace is unknown. In
short, demographic analysis simply moves the question Of liberal shift to a
diﬂ'erent but functionally identical level.

Bias in the media

Any discussion of the interrelationship between the mass media and
the liberalism Of the United States must include consideration Of the aft-
8tated position that the mass media possess a liberal bias (c.f. Efron, 1971;
Keely, 1971, Agnew, 1971); ergo, if the nation has come to move toward the

45

political left, it is as a result of the deliberate machinations of a left-leaning
industry.

Fears in this regard are not completely unfounded; journalism as a
whole is populated by people who are substantially more liberal than
average (Schneider and Lewis, 1985) who are forced by the nature Of their
industry tO "gatekeep" or select speciﬁc news items from the universe of
news items (for instance, see White, 1950; Bagdikian, 1971). In fact, in the
classic White (1950) study that led to the creation Of the gatekeeper
metaphor, the editor in question speciﬁcally did reject certain stories based
on ideology — terming an important human rights story of the day as
"propaganda" and rejecting another as "too red".

Similarly, liberal critics (such as Gitlin, 1980; Cooper and Soley, 1990)
ﬁnd a distinct conservative bias to the media. James (1988), faced with
similar inconsistencies, suggests that this contradiction lies in the method
of journalistic (rather than scientiﬁc) argumentation: a journalist states a
thesis and then presents examples which support the thesis. This
"reasoning from example" seems to be a part Of the "natural logic" of the
human mind (Mineo, 1991), but must be suspect given the demonstrated
tendency Of human beings to prefer material supportive Of their viewpoints.
The genesis of this dichotomy may also lie in the nature of the mass media
industry: While the bulk of media employees are liberal, those at the top Of
the pyramid of “power” are conservative, being members of society’s elite.
This may explain the Observed contradiction that while every day media
content — prepared by those lower on the social rungs — is somewhat
liberal, editorials - over which media employers exert more direct control,
tend to more Often support conservative positions.

Stevenson and Greene (1980) presented students with positive and

46

negative articles about the 1976 presidential candidates and counted the
number of times the students stopped to counterargue (see Carter, Ruggels,
Jackson, and Heffner, 1973). The students stopped more substantially more
frequently in material they perceived as biased, implying that bias is itself a
subjective phenomenon.

To cope with the problem Of subjectivity in estimates of media bias,
researchers have moved to the "objective" techniques of content analysis
(thereby attempting to replace subjectivity with intersubjectivity). A8 a
general rule, these studies demonstrate an extremely small but fairly
consistent liberal bias.

For instance, Russo (197 2) concluded that NBC's and CBS's coverage
Of the conﬂict in Vietnam during the 1969- 1970 period was biased against
the administration by an average Of about one-half of one point on a ten
point scale. Stevenson, Eisinger, Feinberg, and Kotok (197 3) concluded that
the favorability of coverage Of Nixon was roughly equal to that accorded
Humphrey, although Humphrey did receive about 10 percent more
coverage. Lawry's (1974) major ﬁndings included the discovery of a
statistically signiﬁcant number Of anti-Republican to anti-Democratic
statements in the networks during the 1972 campaign — a difference Of 5
percent - and that ABC used more ﬁlm footage Of McGovern.

Robinson (1985) showed that Mondale and Ferraro received about
26,000 seconds of network time versus 25,000 for Reagan and Bush, and that
only 2.5 percent of the statements made contained any issue-based bias; Of
these 21 biased statements, 11 were liberal and 10 conservative. And ﬁnally,
Friedman, Mertz, and DiMatteO (1980) had students code the expressions on
the faces Of ﬁve prominent newscasters as they said "Gerald Ford" or

"Jimmy Carter" (with the audio track out so that the students would not

47

know what was being said). They found a statistically signiﬁcant difference
of 0.21 points favoring Carter, measured on a 21 point scale.

Shoemaker and Reese (1991) cite instances both of journalists who
permit their biases to appear in their reporting, and those who work so
assiduously to prevent such ﬁom happening that they actually
overcompensate and lend support to viewpoints Opposite their own.
Shoemaker and Reese found the results so ambiguous that they were
unable to draw ﬁrm conclusions from them, except to say that some
journalists show some bias at some times.

A second approach to the measurement Of liberal bias in the media
would be to take advantage of the notion that it is a subjective phenomenon
and create intersubjectivity by summing across a representative sample of
subjective responses in the manner similar to that of the Delphi technique
(c.f. Jones and Twiss, 1978). For instance, ABC Survey #0121 (1984) found
that 17 percent of those polled felt that TV news favored the Democrats and
11 percent felt it favored the Republicans; similarly, Schneider and Lewis
(1985) report that 30 percent felt that the news media generally possessed a
liberal bias whereas 13 percent felt they were conservative. Converting
these ﬁgures to z-scores and then taking their midpoints yields the estimate
that the media are in the range of .15 to .30 standard deviations more liberal
than the population average.

Both methods yield the same result: the news media have a small
but measurable liberal bias. Because of this, and because it is necessary to
at least consider the prevailing attitude of media liberalism, in the present
study it will be necessary to measure this bias across time and control for

and measure its impact.

48

PotmtialDrawbacksinﬂreUssofPublicOpinionData

Public Opinion polling has drawn criticism concerning its scientiﬁc
value from two directions. The ﬁrst, summarized by Blumer (1948), is that
the measurement Of public opinion by the random selection Of individuals
and application of inferential statistics, provides an inadequate measure Of
true public opinion because it proceeds from an atheoretic position. The
second, derived from Katz and Lazarsfeld (1955), is that public Opinion
polling obscures the interaction of power groups and Opinion leaders that
lead to the formation Of that opinion; in other words, social structure is
ignored. The purpose Of the present study is, in part, to address this second
concern, by identifying three Of the roots Of public opinion, the policy
agenda, the media agenda, and conditions in the outside “real world” and
measuring their inﬂuence; and while public Opinion continues to be
gathered atheoretically, the measurement process will permit post hoc
theoretical grouping by the process of content analysis (Krippendorf, 1980).

Another criticism of public Opinion as it is currently measured is
that it acts to reduce the participation of the individual in the political
process. As Herbst (1991) has pointed out, earlier in the history of the
nation, in the 18008, for instance, public Opinion was frequently expressed
in unstructured but public ways, i.e. strikes, petitions”, riots, and even the
Whiskey Rebellion and the Fenian invasion Of Canada! Public Opinion
polling, on the other hand, is both structured, i.e. the respondent is limited
in the choices available both in terms Of questions and responses, and
private, meaning that the respondent has no Opportunity for contact (or

discussion) with others in making his or her response. Herbst argues that

 

" The right to petition the government for redress of grievance was speciﬁcally
reserved to the people in the First Amendment to the Constitution.

49

the shift to private and structured measurements of public Opinion weakens
the democratic process by discouraging political discussion and by
encouraging “bandwagon” effects, whereby people give responses which
they they perceive as popular rather than “true” responses. The salience of
this to the proposed study is that it suggests that changes in public Opinion .
might be a result of changes in fashion rather than true changes in public
Opinion.”

Kaplowitz, Fink, D’Alessio, and Armstrong ( 1983) showed that
bandwagon effects did occur on topics with which the respondents were not
personally involved, but did not with subjects they were involved in.
Further, as Luttbeg and Gant (1983) point out, while the electorate describes
itself as being slightly conservative, few members of the populace are able to
Offer a coherent deﬁnition of what that actually means. Thus, the liberal
trend discussed above could be the result Of measurements made on topics
the populace was not involved with combined with respondents picking
response categories that sound popular (or “politically correct”, such as,
“Would you vote for a __ (any minority group) for president?” Since no
minorities have been major party candidates for president, the topic is
uninvolving, and it is a simple thing to give the “popular”, and liberal,
response “Yes”).

The solution to this is to consider changes in behavior as well.
Without getting into the lengthy literature on the attitude-behavior

 

"The validity of Herbst’s conclusion regarding the general trends in the expression of
public opinion may be inadequate. While there was no public opinion polling in the 18008,
the fact is that public, unstructured expressions Of public opinion exist to this day. In the
week this was originally written, in 1992, UAW members sponsored a “car bash” where
people paid for the privilege of hitting a 'Ibyota with a sledge hammer; unidentiﬁed men
were printing “Buy America” stickers and surreptitiously plastering them on imported
automobiles in 'lbxas, and anti-abortionists were praying outside the house of a Kansas-
based abortionist. It may simply be that more avenues are open for the expression of public
oprnron.

50

relationship, it is reasonable to expect that a “real” change in public Opinion
will be followed by a change in behavior of the same type, i.e. the expressed
willingness to vote for minorities will be demonstrated by the increased
election of minorities. If the change in Opinion is merely the result Of

“bandwagon” effects, behavioral changes will not follow.

Expectations

Examining the role Of the mass media concerning the demonstrated
liberal swing within the United States requires long term analysis Of four
major areas: the media agenda, as potential causative agent; public
opinion; the policy agenda, acting as both a potential change agent on its
own and also as a mediating body between the media and public Opinion;
and a variety Of external socioeconomic factors such as inﬂation or
unemployment, some Of which might confound results and thus must be
controlled, and some of which represent the consequences Of opinion
change and thus must be measured to establish the veridicality of that
change.

As a result of the research reviewed above, expectations of the results
Of the present study are:

1) The media will show a direct impact on public

liberalism;

2) The policy agenda will show a direct impact on public

liberalism;

3) The media will show a direct impact on the policy

51

agenda;

4) The increase in public liberalism will be followed by an

increase in liberal activity in the nation.

5) Separate models Of the formulation Of public opinion
will vary ﬁ-0m issue to issue.

All of these expectations were derived from the preceding discussion.
The ﬁrst four are explicitly mentioned above and hopefully need not be
restated here. The ﬁfth expectation is derived from the nature Of the
expected issue network structure: because Of the nature of the coalescence
process, issue networks are formed Of different people who necessarily
make different “tactical” decisions in attempting to communicate their
frame to the mass audience. Some issues, as we have seen (vide Sharp’s,
1992, discussion of the drug war), are driven from the “top” down, by
policymakers. Others are driven from the bottom up, by the concerns of
citizens who belong to issue networks (as the Americans with Disabilities
Act seems to have been). Still others are driven overtly by the media’s
agenda, as was the case with Watergate.

In short, different issue networks with different members and
different access to media and policymakers coalesce around different issues
should yield different models of the interrelationship of public Opinion,

policy agenda, media agenda, and external factors.

Chapter 2

Measurement and. Analysis

As seen in Figure 2 (Theoretical Model), this study examines ﬁve major
variable “clusters” (or conceptual constructs): public Opinion; the agenda Of
the media; the policy agenda; and two sets Of socioeconomic factors, the
inputs and the outputs. Each of these variable clusters must be deﬁned and
measured, as discussed below; in addition, an analytical strategy is deﬁned.

Measurement of Public Opinion
As discussed in the previous chapter, Smith (1990) assembled public
Opinion data on a total of 455 items, each of which had been asked of the
public at least twice, making possible the demonstration Of a net liberal trend
which was presented in Figure 1. Table 1 contains the complete list of 16
content-based sub-categories constructed by Smith, along with the number Of
trends which compose that sub-category (The ﬁnal column, Interrupted?, will
be discussed later in this section).
In classifying responses as “liberal”, Smith reports using the following
content rules:
“. . . Contemporary liberalism is (1) reformist, Opting for change
and generally Opposed to the status quo; (2) democratic,
favoring a full extension of electoral rights; (3) libertarian,
supporting civil liberties such as free speech and the right to
protest; (4) regulatory and interventionist, backing the

management of business and the economy by the government;

52

Factor Name

1

2
3
4
5
6
7
8
9
10
11
12
13

14

ESE-I

53

Table 1

Measurement Of the Factors of Liberalism

Abortion

Civil Liberties (CL)

Crime (CR)

Economic Regulations (ER)
Family

Feminism (FE)

Foreign Affairs and Military (FA)
Labor (LA)

Lifestyles

Miscellaneous

Politics

Race and Ethnicity (RE)
Religion

Sex

Social Welfare (SW)
Spending and Taxes (ST)

Number of 'Itends

10

85398

03
H

8838888353428

Interrupted?
yes
yes
yes
yes
no

yes

. yes

yes

54

(5) centralist, using the federal government to set and enforce
national standards and regulate state and local governments;
(6) humanitarian, favoring a social welfare system for the care
and protection of society in general and the lower class in
particular; (7) egalitarian, advocating equal treatment for all
and perhaps equal conditions for all; and (8) permissive,
tolerating and Often approving of non-traditional lifestyles and
practices . . . Internationally, contemporary liberalism is (1)
internationalist, supporting active U.S. involvement in the
world; (2) multinational, backing the UN and other collective
efforts; (3) nonmilitarist, preferring nonmilitary solutions to
international disputes; and (4) prodétente, advocating good
relations with Communist nations and not emphasizing anti-
Communism as a cornerstone of foreign policy (pg. 481).”1
Using this list as an operational deﬁnition, Smith was able to content
analyze responses to poll items which shared three characteristics: the
item had been asked at least twice; the wording Of the question had
remained roughly comparable across samplings; and the content of the
item had fallen into at least one of the fourteen content areas. He then
scaled the items to yield the data in Figure 1 by summing the annual
proportional change in each item across all items, with changes in the
liberal direction being (arbitrarily) coded as positive. Results for items
which were measured more than once during a given year were averaged;
if a period Of more than one and less than six years elapsed between
repetitions of an item, the results were approximated by linear

interpolation;: if the elapsed time between repetitions of the item was six

 

' This list is inserted here in toto as it will be referred to in other sections of this chapter.

“ Smith (1995) states that assumptions of non-linearity between measurements were
tested but did not make much of a difference.

55

years or more the item was excluded ﬁom the analysis of that year’s data.
(Including these items leads to a long term “smoothing” of the dependent
measure.)

The present study used an updated list of responses to 476 opinion
items, available from the NORC, which extended the original data set by
including additional items and polling results through 1994. Items were
sorted and scaled as above; however, rather than use the cumulative
(summed) ﬁgure as Smith did, the annual average net trend derived from
each year’s data was used instead. Mathematically speaking, using the
cumulated scores leads to a situation where the magnitude of the kth score
is dominated by the ﬁrst through (k-1)th scores, obscuring the annual
“shocks” created by other variables. Using annual scores reduces the
impact of the previous items in the series to an “inertia” or “carry-over”
quantity, if any, and makes the impact of other variables less obscure.

This method of scaling “liberalism” was retained as it possesses two
advantages. The ﬁrst advantage of continuing to use Smith’s scale is that,
based on this deﬁnitional structure, it both reﬂects previous literature and
possesses face validity, which are, of course, two of the expectations of a
useful Operational deﬁnition (Miller and Nicholson, 197 6).

Additionally, the scale possesses the additional advantage of being
horizontally dense, that is, continuously measuring the construct in
question across time. As seen in Table 1, while certain Of the sub-categories
are interrupted (that is, there are periods where none Of the items
composing that sub-category are being presented to the public), as far as the
overall scale at any given time is concerned a minimum of 50 different
trend lines are being measured.

For the purposes of this study, seven of the 16 sub-categories have

56

been eliminated, for a variety Of reasons. The sub-categories of Abortion,
Lifestyles, and Sex possessed items referring to actions whose legal status
changed during the course of the study (for example, abortion,
homosexuality, certain types of drug use, and the wearing of shorts in
public by women). The legal status Of such items has the clear potential to
bias survey results. “Miscellaneous” does not constitute a coherent
classiﬁcation enabling interpretation. Finally, Family, Politics, and
Religion were excluded on the basis of being less than central to the
differences between liberal and conservative thought; that is, while modern
conservative thought stresses religious or family values, this is a fairly
recent stress; and the liberal is certainly not Opposed to the family or God.
(The existence of these content categories indicates that the Liberal-
Conservative dimension is not necessarily unidimensional; note that
Smith’s deﬁnition does not include a “religiosity” factor, for instance.)
Along with the use Of “liberalism” as a single dependent measure,
two of the sub-categories will be selected for more in-depth examination. As
noted above, while the attitude of the public at large has become more
liberal generally, this is not true across all Of the content sub-categories;
speciﬁcally, the public responds more conservatively to questions
concerning Social Welfare, Crime, Spending and Taxation, and also to a
sub-set of the Foreign Affairs and Military items, those dealing with
Military Recruitment (Smith, 1990). This is, in a sense, counter-intuitive: if
the public is becoming more liberal, then it should follow that the public
should be becoming consistently more liberal rather than inconsistently
more liberal; in other words, whatever is causing the majority of the scales
to trend towards liberalism should in principle cause all of the scales to
trend towards liberalism. Selecting a subset of the subscales for closer

57

examination might have the possibility Of revealing patterns of inﬂuence
which might otherwise be obscured by the magnitude of the overall trend. It
will also permit explication and testing Of the ﬁfth expectation.

In considering the selection of sub-scales, it is preferred that the sub-
set meet certain criteria: they should possess a wide variety of internal,
overall trends (in order to gain the advantage laid out in the previous
paragraph); they should take advantage of as many individual trendlines
as possible (to minimize the impact of aberrant data and sampling error);
and they should be continuous, i.e. have greater than 0 active trends, in
order to make eﬂicient use of all of the data on predictor variables.

Satisfaction of these criteria leads to the selection of Race and
Ethnicity and Foreign Affairs for speciﬁc examination (see, again, Table 1).
Race and Ethnicity is the sub-scale with the largest number of items as well
as the largest minimum number of active trends; it also has the second
strongest net liberal trend (after Abortion, which, as above, was excluded
f'rom the analysis due to the confounding effect of its legal status). Foreign
Aﬂ'airs is the only other content area in which data was continuously
gathered, and is of particular interest for the reason brought out above:
opinion has become more conservative on the question of military service.

Thus, liberalism was measured, on a yearly basis, as the overall net
trend for all indicators for that year. Additionally, sub-scales for Race and
Ethnicity, and Foreign Affairs were measured and attempts made to
predict their behavior as well as that of the whole. Table 2 contains the
number Of active trends on a yearly basis broken out by content area, as well
as the gross change in public opinion in that area during that year. (The
Annual Net 'ltend was determined by summing the gross across the
content areas and then the active trends; ﬁnally, the latter was divided into

58

Table 2
Gross Changes in Public Agenda and Number Of Active Trends
By year and Content Area

Year CL CR ER FA FE LA

N Gross N Gross N Gross N Gross N Gross N Gross
1941 0 0 3 -.046 0 1 .026 0
1942 1 .047 0 3 -.046 0 1 .026 2 .028
1943 1 .047 0 4 -.096 1 .045 1 .026 2 .028
1944 5 .053 0 4 -.049 1 -.036 l .026 3 .151
1945 5 .053 0 4 -.015 1 .009 1 .026 3 -.025
1946 4 .028 0 5 .034 2 .095 1 .042 1 .008
1947 4 -. 159 0 6 . 114 4 -.239 1 .042 5 .073
1948 4 -.059 0 6 -. 102 3 .050 1 .042 6 -.204
1949 5 -.298 0 6 -.053 3 .077 1 .042 7 .016
1%0 5 -. 141 0 6 -. 117 3 -.013 0 2 .008
1%1 2 -.027 0 7 -. 150 5 . 119 0 2 .008
1%2 2 -.027 0 6 -.117 6 .320 0 2 .008
1%3 2 -.027 0 6 -. 117 6 .141 0 1 .046
1%4 5 -.03 1 1 .035 5 .069 6 .246 O 4 .071
1%5 3 .033 3 .043 5 .069 7 .256 0 4 .071
1%6 2 -.025 3 .043 0 7 .035 1 .007 3 .037
1%7 2 -.020 3 .067 1 .003 7 .070 1 .007 3 .037
1%8 0 2 -.054 l .003 7 .122 1 .007 3 -.096
1%9 0 1 -.017 1 -.020 7 .093 1 .032 3 .042
1%) 0 2 -.010 4 .035 7 -.026 l -.004 5 -.016
1%1 O 2 .022 3 .055 3 -.001 1 -.004 5 -.016
1962 0 2 .022 6 .012 3 -.092 1 -.004 6 .005
1%3 0 2 .022 6 -.027 4 -.027 1 -.004 5 .081
1%4 0 2 -.021 5 -. 107 5 -. 103 1 .004 5 .046
1%5 0 2 -.021 5 -.037 5 . 118 1 .004 6 .101
1%6 0 6 -.081 10 -.102 7 .096 2 .002 10 .040
1%? 0 5 -.131 10 .155 7 .136 2 .002 9 -.165
1%8 0 6 .009 9 .178 7 .098 2 -.017 8 - . 115
19a 3 -.043 16 -.170 12 .473 9 .211 2 -.017 6 -.042
1970 4 .025 16 -.050 11 .379 9 .066 3 . 111 6 -.005
1971 4 .129 17 .046 12 .037 9 .283 5 .124 7 .036
1972 4 .129 18 -.036 12 .306 7 .021 5 .107 7 .036
1973 14 .337 20 -. 157 12 .249 9 -.002 6 . 113 4 .043
1974 17 -.009 Z) -.078 12 .386 11 -. 154 9 . 110 3 .035
1975 12 -.028 a) -.153 16 .177 12 -.253 12 .044 5 -.052
1976 12 -.037 21 -.251 15 -.033 12 -.343 14 -.066 8 -.147
1977 17 -. 197 Z) -.082 17 -.173 11 .053 15 .001 7 -.131
1978 18 .380 Z) -.015 20 .056 12 -.009 17 .298 8 -.060
1979 18 .046 19 -.002 21 .184 11 -.091 18 -.062 9 .073
m 17 .035 19 -.074 18 -.250 10 -.280 17 .058 9 -.208
1%1 17 -. 118 18 .091 16 -.040 9 . 179 m .223 8 -. 165
1%2 17 -. 118 18 -.206 10 -. 105 8 .241 18 .499 4 .105
1%3 17 127 17 -. 114 9 -.045 9 065 18 252 3 .023

17

5555555555

CL
N Gross

.184
-.313
.188
.208
-.047
.477
.047
.265
.066
.066
.051

55555555555

CR
N Gross

.540
-. 181
-. 140

.010
-.061

.176
-.056

.628
-.207
-. 192
-.020

59

Table 2 (Cont’d)
ER FA
N Gross N Gross
4 -.092 9 .038
4 -. 112 8 .092
3 -. 187 7 .050
2 .190 6 .064
0 6 .122
0 5 .174
0 5 .150
0 5 .316
0 5 -.237
0 5 .120
0 4 -. 124

N Gross

Ocoecococoti'5‘52i55

FE

.016
.137
.152
.191
.246
.035
. 154
. 106
.146
.094
.076

N
3
3
1
0
0
0
0
0
0
0
0

LA
Gross
.008

6)

Table 2 (Cont’d)

Year RE ST SW

N Gross N Gross N Gross
1941 2 -.027 0 0
1942 1 -.015 0 0
1943 2 -.050 0 0
1944 5 -.050 0 0
1945 3 .060 0 0
1946 5 .151 0 0
1947 4 .196 0 1 .010
1948 2 .106 1 -.002 1 .000
1949 3 .108 1 .151 0
1%0 7 .436 1 -. 112 0
1%1 7 .160 1 -.014 0
1952 7 .055 1 -.190 0
1%3 7 .142 1 . 114 0
1%4 6 .089 1 .015 0
1955 4 .020 1 .015 0
1956 4 .061 1 .015 1 .020
1957 5 -.173 1 -.060 4 .042
1%8 7 .136 1 .049 4 -.001
1%9 11 .302 1 .049 4 .003
1960 10 .085 1 .027 4 .003
1961 9 .093 1 .027 1 -.059
1962 7 .030 1 -.015 1 -.011
1963 7 .030 1 -.052 0
1%4 24 .333 1 -.035 0
1965 3) .594 1 .021 5 -.083
1966 33 .274 1 .021 5 -.023
1967 I5 -.172 1 -.061 5 -.023
1968 32 .551 1 -.055 5 -.002
1969 3'3 .758 1 -.055 3 .108
1970 33 .684 7 .013 4 .148
1971 34 .759 8 .023 5 .188
1972 34 .600 18 -.083 5 .163
1973 31 .235 E -.098 6 .051
1974 a) .292 % -.210 6 .132
1975 so -.045 % -.322 7 .006
1976 ii) .227 m -.214 7 -.078
1977 29 .181 14 -.341 7 -.014
1978 33 .338 14 -.014 7 -.199
1979 a .173 14 -.241 7 .031
1%) 5 .184 14 -. 110 7 -.082
131 ﬁ .223 15 .380 6 -.072
1%2 5 .201 16 .454 4 -.027
1%3 5 .080 17 .149 4 -.025
134 23 .316 17 .410 6 -.019

61

Table 2 (Cont’d)

Year RE ST S W

N Gross N Gross N Gross
1%5 22 -.069 29 .122 7 .023
1% 21 .152 29 -.072 7 .023
187 22 .163 27 .309 7 -.050
1%8 2 . 167 27 . 199 7 .031
1%9 22 .300 w .385 7 .127
1990 23 .012 % .223 7 . 113
1991 22 .216 m -.685 6 -.008
1992 21 .078 m .319 6 -.079
19% 18 .109 25 .046 4 -.072
1994 15 -.013 % -.480 4 -. 155

the former.)

Determining the Media Agenda

The media agenda is perhaps the most difﬁcult factor to reconstruct
historically for two reasons. First, many media, especially the electronic
media, are essentially ephemeral in nature; unlike the books in a library,
the broadcast signal waits for no man and it is ﬁ'equently neither easy nor
desirable to store it. Unfortunately, people access broadcast media far more
frequently than they do print media (Bower, 1985).

Second, the sheer mass of data makes the measurement and
evaluation of the content of any medium problematic. A one month archive
of even a small daily paper creates a stack of newsprint in excess of a foot
high, and a 45 year archive ﬁlls two or more microform drawers.

Fortunately. the Beaden’e Guide in Periodical Literature has been
demonstratedly effective to the researcher interested in approximating the
historical media diet (c.f. Funkhouser, 1974; D’Alessio, 1992). It attempts to
index and classify by content a wide variety of magazine articles. The scope
of the contents of the Bender-Le Guide is deliberately exhaustive rather than
restrictive; rather than representing a sample, the Reader-Le Guide
attempts to represent a population. The potential problem with using the
Readeﬁe Guide as a source is that articles from all sources are counted
equally and not weighted by circulation ﬁgures. However, some of the data
presented in Chapter One suggest that the media agenda functions as a
group or cluster and not as a series Of individual stories (for instance, in
that media impacts build up over a period of months); thus, there is a
degree of correspondence between the number of articles appearing on a

topic and both its importance and potential impact - “bigger” stories attract

63

more attention, and thus a larger number of articles. Although the
Beadeﬁe Guide only directly represents the contents of periodicals and not
those of newspapers or television, the time and space constraints of the
news media (Friendly, 1975; Bagdikian, 1971) ensure a fairly large degree of
overlap across the content of all three media.

Testing the impact of the media involves the evaluation Of persuasive
trends within the media. This was accomplished by coding a sample from
the articles listed in the W Guide as relevant relevant to each of the
content areas; a random selection of the articles was recovered from
archival ﬁles Of the the medium in question. The exact number of articles
in each yearly sample was calculated to yield results of 3:25 percent
accuracy. The exact list of content areas articles were selected from appears
as Table 3.

Coding was done by at least two judges for each article. A coding
instrument derived directly from the operational deﬁnition of “liberalism”
presented earlier was constructed (it is attached as Appendix C); coders
were asked to read the each article looking for statements which were
overtly biased along any of the lines discussed by Smith and listed earlier,
and to make a simple raw count of statements biased toward either side.
The number of liberally-biased statements (L’s) and conservatively-biased
statements (C’s) were separately summed and a liberalism score for the
article was constructed by subtracting the number of C’s from the number
of L’ s .

Coder training consisted Of a lengthy (ca. one-half hour) discussion of
each of the bias areas, including several historical examples of each, at
least one from each side. Coders were then presented with an article

containing a known number of biased statements on each side; they coded

64

Table 3

Topic Headings used in Readeﬁe Guide

Civil Liberties
-- Civil rights
-- Due process of law

Crime
-- Crime and criminals
-- Crime and criminals, U.S.

- Assault
-- Sex crimes

Economic Regulation
- Government Regulation of Industry
-- Prices - Regulation
-- Prices - Regulation - US

Feminism
-- Feminism
-- Woman - equal rights
-- Woman - employment

Foreign Affairs
-- United States - Foreign Relations
-- United Nations

Labor
-- Strikes
-- Trade Unions
-- Labor Unions

Race and Ethnicity
-- Race Prejudice
-- Race Discrimination
- Negroes (Blacks after 1971)
-- Negroes in the US - Segregation

-- Free speech
-- Privacy

-- Burglary and burglers
-- Murder
-- Rape

-- Industry and State
-- Wage-Price Policy

-- Equal pay for equal work
-- Women’s liberation movement
-- Woman - Occupations

-- Conscription - US
-- Military Service, Compulsory

-- Strikes - US
-- Trade Unions - US
-- Labor Unions - US

-- Race Problems

-- Civil Rights Demonstrations

-- Race Riots

-- Discrimination in Employment

-- Negroes in the US - Resistance to Segregation

-- Negroes in the US - Civil Rights

Social Welfare
-- Poor Relief
-- Social Welfare
-- Economic Assistance, Domestic

Spending and Taxation
-- Taxation
-- Government Appropriations
- Income Tax - US

-- Public Welfare
-- Public Welfare - US

-- Taxation - US
-- Budget
- Income Tax

-- United States - Appropriations and Expenditures

65

it, and the results were discussed. This process was repeated on a second
sample article. Coders were cautioned to be careful not to associate either
liberalism or conservatism a priori to either major political party, and also
to be careful to stick to the historical criteria and not diverge into recent
debates (about, for instance, media bias, which appears to be more a
function Of the party in power and not necessarily a liberal-conservative
issue; Page and Shapiro, 1992). The performance of the coders was
reviewed periodically, and questions answered as they arose. Coders were
paid $5 per hour at the beginning of the study; later this was raised to $6.50.
Conﬂicts between scores assigned by coders were handled in one of
two ways. If the difference between the scores was three points or less, the
two scores were averaged. If the difference was greater than three points,
the conﬂict was resolved by having the article coded by a third coder. (The
“three points” rule was arrived at by the decision that it was acceptable for
coders to disagree on the valence of one statement and for one Of the two to
see one more statement as overtly biased.) Table 4 contains the mean net

bias scores, broken down by year and content area.

Measuring the Policy Agenda

In everyday circumstances, the government exerts day-to-day
inﬂuence on the population through the mechanism Of legislation. As
Schlesinger (1939) noted, this can include legislation designed speciﬁcally
to move the country in a speciﬁc societal direction; for instance, to move the
country in a liberal direction by making, for instance, racial or sexual
equality the “law of the land”.

This law has essentially two sources: the Congress, and the

President and sitting administration, which can publicly request or oppose

Year

CL
1.3
1.5
1.5
2.8
2.0
3.9
2.1
6.9
1.3
1.1
0.9
1.5
0.0
0.9
2.9
1.0
1.8
2.1
-0. 1
2.1
0.2
2.6
1.3
1.3
1.8
0.3
2.1
3.6
5.3
6.7
2.4
1.8
2.3
2.2
2.3
1.7
1.0
0.8
2.8
0.6
1.3
2.0
2.1

as

Table 4
Mean Media Bias
By year and Content Area

CR ER FA FE LA
0.6 0.7 2.0 2.8 -0.3
-0.6 0.5 2.5 1.4 0.4
0.4 -1.4 3.1 1.6 0.2
1.5 0.5 1.2 2.4 2.0
-0.5 0.1 -0. 1 1.8 0.8
0.1 0.1 0.5 2.1 0.6
0.3 2.0 1.6 2.8 0.0
0.4 0.6 -7. 1 0.0 0.2
0.5 -1.0 0.7 -0.4 -1.2
0.1 0.0 -0.2 -1.0 0.6
0.3 0.1 -0.6 0.9 0.5
0.3 -l.l 0.0 1.8 0.1
-0.3 0.4 2.5 1.2 0.2
0.4 0.5 1.6 1.5 0.9
0.3 1.0 1.5 2.0 0.8
0.0 -2.3 0.4 -0.3 0.3
0.9 0.0 -0.9 1.0 0.2
0.3 0.6 -1.3 2.6 0.8
0.0 -1.8 0.2 0.6 0.4
0.1 0.8 0.3 2.1 0.3
-0. 1 -0.4 1.5 1.3 -0.2
0.2 0.9 1.6 1.9 0.8
0.1 -1.7 0.3 1.6 -0.5
-1. 1 -0.9 3.0 0.1 0.7
-1.3 -0.6 0.7 6.8 0.9
0.1 0.6 2.3 3.8 3.3
0.1 1.3 1.6 2.7 0.4
-1.5 2.1 1.4 -2.1 -0.3
-0.5 1.5 -1.8 2.6 3.1
0.1 -2.5 1.2 1.4 0.2
0.5 -0.4 1.8 1.9 1.5
0.5 -0.4 1.1 3.6 0.0
0.9 1.2 2.3 2.3 1.0
0.5 -2.3 1.2 3.0 0.8
-0.6 0.0 -1.2 1.2 -0.2
0.1 -0.4 3.0 1.7 -0.7
0.0 1.2 -0.3 1.3 0.8
1.6 -0.6 -0.3 1.9 0.1
-0.4 0.2 -0.8 2.8 0.1
-0. 1 1.1 -3.0 0.9 0.6
-0.4 -0.9 0.6 0.4 0.3
0.0 -3.0 1.3 0.3 0.6
-0.1 2.9 -1.2 1.8 -0.1

RE
7. 1
1.6
1.7
2.3
3.0
2.4
1.4
0.8
2.3
2.0
1.8
2.3
1.6
3.0
0.4
2.1
1.6
1.3
4.4
2.3
1.8
0.0
2.8
1.0
2.8
1.5
4.1
9.3
2.7
4.2
1.2
2.0
5.8
0.5
1.3
3.4
0.7
1.3
0.8
1.9
1.9
1.3
0.6

ST
0.4
-0.3
-0.2
1.2
-0.4
0.8
-0. 1
-0.3
-0.8
-0.5
0.1
0.5
0.4
0.2
-0.4
0.7
-0.4
0.3
0.0
-0.2
- 1.0
0.7
1.2
1.0
0.0
0.8
0.6
0. 1
0.3
1.9
-0.5
1.9
-0.3
-0.6
0.0
0.6
-0.7
1.2
0.0
-0.5
0.9
-0.6
0.5

S W
2.8
2.6
2.0
1.2
3.5

2.5
-0.6
2.1
3.3
0.0
3.5
1.2
1.3
3.3
-2.0
1.3
-0.6
0.3
2.3
1.3
-0.3
4.4
0.4
2.5
1.8
0.7
0.0
-0.6
-0.7
-0.4
-1.3
-0.6
0.4
-0.4
-1.3
1.4
0.4
0.6
1.1
2.6
0.9
1.6

1.7
5.9
-0.7
1.1

0.3
0.0
0.4
0.0

67

Table 4 (Cont’d)
1.0 3.4 1.2
3.6 0.5 2.5
1.3 2.0 1.1

-1.9 2.3 3.1

0.6
1.1
0.4
1. 1

1.4
1.9
2.1
1.7

-0.2
-1.1

1.1
-0.7

0.5
1.4
0.3
1.7

68

legislation and which possesses veto power. (The Supreme Court also
contributes to this process, but its contributions tend to be delayed and
diffuse).

Both the administrations’ activities and those Of the Congress in the
relative content areas as recorded in WW1; were
examined and scored. In the absence of a prior literature in this area, a
simple scoring system was devised. For congressional actions:

* Action (hearings, passage of a bill, etc.) in either single house of
Congress was scored as one point (valence was assigned accordingly, i.e.
defeat of a liberal bill is scored as a conservative point);

* Simultaneous action in both houses was scored as two points;

* Three points were scored if the completed bill reached the
President’s desk for signing or veto - it turns out that numerous bills
“disappear” in the process of reconciling Senate-and House versions in
conference;

* Four points were scored if a Presidential veto was overridden to
enact a bill.

For administration activities, each action initiated by a sitting
administration (calling for legislation; vetoing legislation; proposing
legislation) was scored as one point in the appropriate direction. Note that
signing a bill into law was not counted as an action, as the vast majority of
bills are signed; if the administration originated the bill, it was counted as
above, as having been proposed. This limits the score for the administration
to those issues on which it has taken a public stance. Similarly, legislation
passed at the request of the administration was counted only for the
administration and not double counted in Congress’s score. Table 5

contains the gross yearly scores for congressional activity broken down by

Table 5

Congressional Activity
By year and Content Area

131226033216322265119033m0m8m6014011334n303656
. . . 1. 1 ..

SW

ST
-7
0
-1

—

-14

0
-1
1
-2

RE

-4

LA
2
-6

-11

0

-1

FE

FA

M51300633£0010212301000002360536030340404313001

0

“000004430 03009..

-3

8
.

-1
-2

43.01”.233223243323000wd—410w1uﬁoo3

as 4884208

-2

L14454 0102293181030107323133330605
C. .. . ... .

-16
-1
-10

Year
1945
1946
1947
1948
1949
1950
1%1
1952
1%3
1954
1%5
1956
1%?
1958
1%9
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1%
1%1
1982
1%3
1%4
1%5
19%
1%?
1988
1989
1990

70

content area. Table 6 contains the same for the administration’s activities.

Sodoeoonomic Factors

As discussed previously, two sorts of external socioeconomic factors
should be considered part of a complete predictive model concerning the
impact of media and other variables on public opinion. The ﬁrst of these
factors is the Socioeconomic Inputs, variables whose actions are so
fundamental as to essentially act as causes of shifts in the public’s agenda.

Economic and social factors have the potential to impact the
liberalism of the nation by virtue of their obtrusiveness (or pervasiveness).
An example is inﬂation: when the prices go up, virtually everybody is
aware of it. Poor economic conditions can be expected to act to decrease
liberalism because the responses to adverse economic conditions, for
instance, isolationism, denigration of foreign products and by extension
foreigners, and/or strife based on regional and racial origins, are more
closely associated with the opposite of liberal viewpoints. The Statistical
Abstract gfthg United States contains yearly data on the Consumer Price
Index (CPI); while the inﬂation rate is not given directly, it is readily
calculated from the tables of the progress of the CPI throughout the time
period in question (see Table 7).

Similarly, the Uniﬁed Crime Rate (again, available in the Statistical
Abstract), might function in the same way, although on a separate factor of
liberalism. The overall liberalism scale includes items on capital
punishment, suggested penalties, and the like; the higher the per capita
crime rate, the more likely one would expect that the populace would
respond more conservatively, at least to that subset of items.

This reasoning led to the development of the following criteria for

Table 6
Administration Activity
By year and Content Area

0
-1
-1

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0

1

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-1

2160
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0
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-2
-3
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-4
-2

E0116011021131030436521332010000400014040

-3
-1
-2
-1
-1
-1

R

-1
-1
-1

M041111034311200120422200340440n19w30015604401
M1401...23.0-0.434..20420042441010423320143340443.016.4243

72

Table 7
Socioeconomic Inputs

By year and Input Area

Ind. Seg Ind. Seg Crime Inﬂation Unemp Major Per Capita

Year Blacks Women Rate Rate Rate Strikes Inc. 'lhx
1944 .281 .NA 114 NA NA NA 18.3
1945 .275 .315 132 NA 1.9 X 19.0
1946 .268 .334 142 8.5 3.6 X 16.3
1947 .262 .352 140 14.5 3.9 249 14.4
1948 .309 .348 136 7.6 3.8 222 14.2
1949 .315 .344 138 -0.9 5.9 232 12.1
1%0 .320 .340 133 1.0 5.3 371 11.3
1%1 .304 .358 128 7.9 3.3 356 12.8
1%2 .338 .367 139 2.3 3.1 3% 15.9
1%3 .318 .346 145 0.8 2.9 361 16.7
1%4 .298 .360 147 0.3 5.6 216 16.1
1%5 .310 .351 136 -0.3 4.4 $0 15.4
1%6 .311 .357 137 1.5 4.2 2% 16.9
1%? .314 .361 141 3.4 4.3 215 17.6
1%8 .318 .371 148 2.8 6.8 $2 16.4
1%9 .313 .361 147 0.9 5.5 183 16.9
1960 .305 .351 159 1.1 5.4 163 18.2
1961 .317 .350 156 1.0 6.? 140 17.9
1962 .308 .348 161 1.0 5.6 149 19.3
1963 .297 .349 166 1.3 5.7 1% 19.6
1%4 .286 .346 188 1.3 5.2 1% 19.5
1965 .284 .350 1% 1.6 4.4 182 19.0
1966 .266 .348 217 2.8 5.5 216 20.8
196? .264 .347 $0 3. 1 4.5 $3 22. 1
1968 .252 .344 2% 4.2 3.6 $8 23.5
1969 .236 .342 329 5.5 3.5 268 27.9
1970 .226 .345 363 5.? 4.8 245 27.1
1971 .220 .338 396 4.4 5.9 1% 24.4
1972 .210 .349 402 3.2 5.6 157 $.7
1973 .197 .349 418 6.2 4.9 197 26.2
1974 .195 .348 461 11.0 5.6 an 26.9
1975 .174 .344 481 9.1 8.3 144 23.1
1976 .181 .342 460 5.8 7.6 140 25.2
1977 .174 .344 467 6.5 6.9 179 28.3
1978 .162 .345 4% 7.6 6.0 1% 29.7
1979 .177 .346 548 11.4 5.8 138 31.8
1% .185 .338 59? 13.5 7.0 1% 31.0
1%1 .178 .335 5% 10.3 7.5 33 32.7
1%2 .183 .330 571 6.2 9.5 54 31.6
1%3 .172 .325 538 3.2 9.5 45 29.3
1%4 .173 .333 539 4.3 7.4 :5 28.9
1%5 .165 .336 55? 3.5 7.1 :1) 31.0
1% .166 .336 618 1.9 6.9 (B 31.4

Blacks
.161
.173
.160
.156
.153
.156

Ind. Seg Ind. Seg
Women
.333
.329
.326
.325
.325
.327

73

Table 7 (Cont’d)

Crime Inﬂation
Rate Rate
610 3.6
637 4. l
663 3.4
732 6.9
758 NA
NA NA

Unemp
Rate
6. 1
5.5
5.2
5.4
6.6
7.3

9

Major Per Capita
Strikes Inc. Tax

$ 33.8
21 32.3
27 35.2
23 32.6
N A NA

NA NA

74

adding a variable to the list of socioeconomic inputs:

1) The variable must be obtrusive;

2) The variable must be tied directly to one or more of the content
areas;

3) Changes in the variable can be linked logically to either
conservative or liberal ideology.

There is in addition the practical requirement that data on the
variable had to be recoverable, whether directly from the literature, via
computation ﬁom raw data, or via extrapolation between points not
removed chronologically by more than ﬁve years.8

Both the annual Inﬂation Rate and the Uniﬁed Crime Rate meet all
the criteria, the Uniﬁed Crime Rate being available in annual issues of the
Statistical Abstract and the annual Inﬂation Rate calculated from
Consumer Price Index data, also published annually.

Five other variables meeting the criteria were selected for inclusion
in the socioeconomic inputs:

* The Unemployment Rate, published annually in the Statistical
Abstract, whose impact on opinion can be expected to be similar to that of
the inﬂation rate.

* The Number of Major Strikes‘ per annum. This should be tied to the
content area of Labor; and one would expect members of the public at large
to be less sympathetic to organized labor as they are affected by the strike in
progress. While the obtrusiveness of any given major strike might be low,
the time period encompassed by the study contains a wide assortment of
strikes which had major impact on the lives of the public, including strikes

 

’ Decennial census data, therefore,would be deemed insufficient in resolving power
for inclusion.

‘The Department of Labor deﬁnes a major strike as one in which 1000 person-days of
work is lost.

75

in the rail, coal, newspaper and music industries, and the raw number of
major strikes called annually (the range across the course of the study is
from a low of 21 in 1988 to a high of 395 in 1952) ensures widespread impact.
(There is a slight dislocation in the strike data due to the prohibition on
strikes in certain industries which was in force during and just after World
War II.)

The Number of Strikes per annum was corrected for the growth of
the population across the time period in question, on the reasoning that the
growth of the population was directly tied to the growth in industrial units;
thus, all other things being equal, a larger population should generate a
greater number of strikes.

* Amount of Individual Income Taxes paid. Again, the magnitude of
this would be expected to directly inﬂuence opinion on Spending and Taxes;
it is clearly obtrusive in that it affects every household and sometimes
multiple members of a household. The amount of income to the government
from individual tax returns is reported in the Statistical Abstract; and these
ﬁgures converted to a per capita ﬁgure by dividing through by the
population. Additionally, the ﬁgures were corrected for inﬂation (as
inﬂation had already been entered into the equation);

* Industrial Integration of Blacks: it is established that, all other
things being equal, people are more likely to like (i.e. have positive opinions
of) people with whom they have contact (c.f. Perry, 1990). This is most likely
to occur, involuntarily, in what has been termed “second” (or work) spaces,
more so than in “ﬁrst” (home) or “third” (social) spaces (Oldenberg, 1989).
Thus, as the work force becomes integrated, more of the population has
direct contact with people from different cultures. Increases in industrial
integration should lead via propinquity to impacts on Race and Ethnicity.

76

Measurement of the integration of the work force has been dealt with
in the literature on labor and industrial relations, with King (1992)
nominating Duncan’s dissimilarity measure (Duncan and Duncan, 1955)
as the most common measure of segregation between ethnic groups across
industrial categories. Data on the distribution of blacks and/or minorities
across occupational category has been available in the Statistical Abstract
annually since 1954, and a variety of other sources provide data for the
years 1944, 1947, 1948 and 1950-1952. Dissimilarity statistics were
calculated for each year for which data was available, and interpolated for
those in which they were not. In order to conform to the direction of the
other Socioeconomic Inputs, the dissimilarity measure was retained
instead of being converted to a similarity measure, as, as with the other, a .
greater degree of dissimilarity should be associated with less propinquity
and thus lower opinion on the topic.

* Industrial Integration of Women: the reasoning for inclusion of
this variable is similar to that for the inclusion of Integration of Blacks,
with the obvious difference that many households have regular contact with
women in ﬁrst and third places. This variable is tied directly to the content
area of Feminism and was treated in the same was as Industrial
Integration of Blacks, except that data on the distribution of females by
occupational category was available for 1953, and not available for 1948 or
1961.

As with inﬂation and the Uniﬁed Crime Rate, annual ﬁgures for the
other socioeconomic inputs are provided in Table 7.

Finally, the discussions in the ﬁrst chapter lead to the notion that, in
order to be “real” (rather than “lip-service” or a bandwagon eﬂ'ect), changes

in public opinion have to eventually manifest themselves in changes in

7'7

public behavior; speciﬁcally, a more liberal public opinion needs to be
followed by more liberal behavior. Table 8, for instance, includes a year-by-
year listing of the number of minority and female members of Congress,
this being an indication of liberal behavior in the areas identiﬁed by Smith
as “democratic” and “egalitarian”.

Again, each of these variables had to meet the criteria of being
directly tied to a content area, being recoverable, and being tied to an
ideological position; other variables which proved impossible to include due
to a lack of available data include such items as the number of handguns in
the nation.

Variables recovered, besides the election of minorities and women to
Congress (tied to Race and Ethnicity and Feminism, respectively),
eventually included:

* Amount of Annual Donations to United Way: Coming out of Social
Welfare, these ﬁgures were available for many years in the Statistical
Abstract and later in (ﬁxing USA, a publication of the AAFRC Trust (1981-
1990). The ﬁgures for annual dollar amounts of donation were corrected for
both inﬂation (to provide a constant dollar basis for comparison) and the
growth of the population (on the grounds that a larger population both
requires more services and provides for more potential donors)“

* Union Enrollments: Tied to Labor, estimated total Union
Enrollments were also available for many years in the Statistical Abstract.
While these estimates were unavailable for much of the 1980’s, Chang and
Sorrentino (1991) provide a different set of estimates for the period of 1975
through 1990. The period of overlap made possible the calculation of a

correction factor designed to reconcile the two estimation procedures (in the

 

‘ It is worth noting that the United Way scandal falls outside the scope of this study and
thus did not inﬂuence these data.

78

Table 8
Socioeconomic Outputs
By Year and Output Area
Election of Election of United Way Union Relative Pay
Year Minorities Women Donations Enrollments women to men
1944 4 8 NA 14.6 70.8
1945 4 8 221.0 14.8 69.4
1946 4 8 171.5 14.1 68.1
1947 4 8 128.3 14.2 66.1
1948 4 8 120.0 13.6 ‘ 65.6
1949 4 10 125.9 13.3 65.4
1%0 4 10 126.5 13.1 65.4
1%1 4 11 126.5 14.4 64.5
1%2 4 11 137.4 14.1 63.6
1%3 4 15 147.5 14.8 63.2
1%4 4 15 157.3 14.7 63.6
1%5 5 1? 162.4 14.2 62.5
1%6 5 17 178.0 14.5 63.4
1%? 4 15 186.8 14.2 63.7
1%8 4 15 196.2 13.? 62.9
1%9 5 17 196.5 13.6 60.6
1960 5 17 207.8 13.2 59.6
1961 6 17 207.6 12.4 58.4
1962 6 1? 211.9 12.4 58.5
1963 7 13 216.2 12.3 59.4
1%4 7 13 219.0 12.4 59.5
1%5 10 12 227.5 12.6 59.4
1966 10 12 247.3 12.9 57.3
196? 11 11 240.0 13.1 57.7
1968 11 11 246.0 13.3 58.2
19% 15 11 245.3 13.3 60.3
1970 15 11 244.7 13.4 59.1
1971 19 13 237.9 13.1 59.3
1972 19 13 234.? 13.1 57.2
1973 22 14 232.0 13.3 56.0
1974 22 14 221.? 13.8 57.5
1975 24 19 210.0 13.9 58.1
1976 24 19 212.4 13.6 58.9
197? 22 18 216.2 13.7 57.9
1978 22 18 216.1 13.3 58.3
1979 21 17 208.0 13.0 58.5
1% 21 17 194.0 12.1 59.2
1%1 23 21 191.9 11.3 58.4
1%2 23 21 188.7 10.9 59.8
1%3 29 23 198.0 10.6 61.8
1%4 a; 23 207.9 10.3 62.6

79

Table 8 (Cont’d)

Election of Election of United Way Union Relative Pay
Year Minorities Women Donations Enrollments women to men
1%5 30 24 213.3 10.2 63.2
1% so 24 219.4 10.0 63.0
1%7 34 25 223.6 10.0 63.9
1%8 34 25 228.4 9.9 65.0
1% 34 27 235.5 9.8 66.8
1990 34 27 226.6 9.6 69.7

80

form of a corrective multiplier); the corrective multiplier was applied to the
Chang and Sorrentino data to bring it into line with that from the Statistical
Abstract. These ﬁgures were then corrected for population growth, on the
assumption that a larger population created a larger pool of persons to be
recruited from;

* And ﬁnally, Women’s Pay (expressed as a fraction of Men’s Pay),
was derived from the document “Earning Differences between Women and
Men” (Department of Labor, 1993), which provides data on the average
earnings for men and women annually for the 1951-1992 period; relative pay
was arrived at by dividing the average annual earnings of women by that of
men. The annual averages for the period 1945-1950 were arrived at by linear
extrapolation of existing trends in the data.

As with the number of female and minority Congressmen, annual
ﬁgures for the other socio-economic output variables are tabulated in Table
8. The creation operational deﬁnitions for the theoretical variable clusters
shown in Figure 2 leads to the expanded or “measurement” model laid out

in Figure 7.

Method of analysis

As time series data is approached with relative infrequency in
communication research (Bruneau, 1994), there seems to be little
agreement on appropriate statistical analysis of it. The analysis of time
series is generally approachable from one of three directions, that is,
multiple regression approaches, autoregression approaches, and what
might be termed composite approaches. Cook, Dintzer, and Mark (1980)
outline four speciﬁc procedures appropriate to the analysis of time series
data which subsume two of those directions.

81

  
   

  
    

  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

     

    

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82

The ﬁrst method overviewed by Cook, et al., is the use of Ordinary
Least Squares (OLS) estimation; that is, the dependent measure is
regressed onto the independent measures in the well-known manner of
multiple regression. In order to determine causal ordering, the dependent
measure is regressed onto the independent measures at previous time
periods, with the expectation that if the lagged measures possess
substantive predictive power even when the synchronous measures are
controlled for, then the independent measure possesses some form of
causal priority over the dependent measure.

Cook, et al.’s, assessment is that OLS is inadequate to the task of
testing the mutual impact of time series for two mathematical reasons.
The ﬁrst is that inadequate de-trending of data can leading to the
measurement of spurious relationships between otherwise unrelated
measures trending coincidentally (or because of mutual causation by a
third, also trended, variable); the second is the possibility of unmeasured
but interrelated variables creating autocorrelated error terms (see Kenny,
1979). The former has the potential to artiﬁcially inﬂate beta weights, and
while the latter does not affect the OLS estimators, it does deﬂate the
standard error of those estimators, leading to overly liberal signiﬁcance
tests (Hibbs, 1974; the presence of an autocorrelated error term can be
detected by the presence of a signiﬁcant Durbin-Watson (1 statistic for the
analysis, or by Durbin’s h under certain circumstances).

The second procedure overviewed by Cook, Dintzer, and Mark is that
of Generalized Least Squares (GLS; see Ostrom, 1978), which is the general
case from which OLS estimation is derived. GLS estimation corrects for
autoregressive error by estimating the coefﬁcient of the autoregressive

error, and using that estimate to correct the original series to remove the

83

autoregressive component of the error terms ﬁom the original time series.
Cook, et al., comment that GLS is potentially ﬂawed in that a) if the
autoregressive correlation in the error terms is higher than ﬁrst order it is
unlikely to be completely corrected for, and b) the technique makes a priori
assumptions about causal ordering.

It should be noted that for the proposed study, however, that a) an
improperly corrected autoregressive error will still yield a signiﬁcant test of
correlated error terms, and that b) the causal ordering of variables has been
largely determined in the prior literature; what is at issue herein is their
interrelationship, largely in terms of relative magnitude of impact. Thus it
may not be useful to reject the use of GLS estimation techniques for this
particular study at this time.

Cook, Dintzer, and Mark continue with a discussion of Auto-
Regressive Integrated Moving Average (ARIMA) models (Box and Jenkins,
1976), which are ﬁrst designed to describe the behavior of a single time
series across time, speciﬁcally, in terms of autoregressive and moving
average components. Thus, if there is presumption that X causes Y, the
ARIMA structure of X is determined and then both series are
“prewhitened” or de-trended using this structure. Finally, a transfer
function which estimates the impact of X on Y at given (or for all) time lags
is calculated.

Cook, et al., point out, however, that use of the ARIMA model for X in
pre-whitening Y may be inadequate in two regards. First, it again
assumes the causal priority of X over Y. Second, they point out that the use
of X’s ARIMA model might inadequately pre-whiten, leading again to the
diﬁculty of spurious relationships based on a common, but not causal,
trend being calculated between X and Y.

84

In order to eradicate the possibility of common trends indicating
spuriously large causal relationships between variables, and additionally to
assist in determining the question of causal priority in systems where it is
unknown, Cook, Dintzer, and Mark, following the lead of Granger (1969),
recommend constructing an independent ARIMA model for each variable
in question, separate pre-whitening based on each variable’s speciﬁc
model, and then calculation of transfer functions. This procedure both
completely de-trends each variable (at least to within the capability of the
ARIMA method), and also obviates the necessity of identifying one variable
as the cause of the other.

Unfortunately, this procedure also carries with it the danger of
obscuring true causal relationships. There do exist variables whose value
at a given point in time are dependent directly on their value at a previous
point in time; for instance, the early stages of the spread of a disease
through a large, geographically homogeneous, and non-immune
population. The number of cases which will occur is directly a function of
the number of carriers, i.e., the number of cases which have occurred. In
this case, a second variable which was similarly trended, for instance, the
average daily temperature during a springtime outbreak of the disease,
would yield spurious indications of causal priority if both series were not
properly de-trended.

However, consider the alternative case, of a variable whose value is
solely dependent on the value of a second variable at a previous point in
time; in continuing with the health care example presented above, let us
say the number of dollars spent on the care of the victims of that
hypothetical disease (the genesis of the time lag being in the time needed for
patients to demonstrate symptoms, and also that needed by the health care

85

system to generate billings). The ARIMA models will not be a perfect
match; speciﬁcally, there will be a small discontinuity at the very beginning
of the models, where the ﬁrst people are becoming ill but as yet no health
care dollars are being spent on them; but for a long epidemic they should
match quite closely. When the second (health care dollars) time series is
pre-whitened, almost all of its variability will be accounted for by its own
previous behavior, and thus it will be assumed, incorrectly, to be a nearly
perfect auto-regressive series just like the ﬁrst time series.

Krull and Paulson (1977) advocate a third process, which forms, in
essence, a synthesis of the ﬁrst two: the dependent variable is in effect “pre-
whitened” as part of its own prediction equation by including itself, lagged,
in the prediction equation as part of a Least Squares analysis. (Although
mute on the speciﬁcs, Krull and Paulson advocate careful observation of the
Durbin-Watson statistic, as well as Durbin’s h, which measure the
correlation between the error terms, implying that GLS techniques be used
if this statistical “pre-whitening” is insufﬁcient.) Appropriate (i.e.
signiﬁcant) lags of independent variables are derived from analysis of a
cross correlation matrix of independent variables at various positive and
negative lags with the dependent variables. Together with the results of the
autoregression analysis of the independent variable, a predictive model is
derived and tested. This is also consistent with the medthods employed by
'Irumbo (1995).

A commonly accepted (Smith, 1980) test of time series models is
provided by the logic of Granger’s (1969) comment that “a perfectly
deterministic series, that is, a series which can be predicted exactly from
its past terms such as a non-stochastic series, cannot be said to have any

causal inﬂuences other than its own past (pg. 430).” Granger called for

as

tests of ﬁt based on the variance of the error of the dependent variable
regressed onto the universe of variables being less than the error created by
the regression of the dependent measure onto that same universe minus
the proposed causal variable. (In other words, that the proposed cause have
predictive power after all other variables have been controlled.)

This position is clearly based on the rationale of protecting the body of
knowledge against Type I error, that is, the possibility that, due to sampling
or measurement error, the researcher will reach the conclusion that a
relationship exists where in reality none does. Like many such tests,
however, it does so at the cost of increasing Type II error, the error made
when the conclusion is drawn that no relationship exists when in reality it
does, such as that which would result in analyzing the hypothetical health
care situation as presented above. Despite the fact that one variable was
completely caused by the other, the conclusion would be that it was
autoregressive, which is, after all, simply another false positive, albeit of a
diﬁ'erent, arguably more parsimonious, sort.

Historically, this position derives from the attempts of logical
positivism to create a form of objective research by making decision making
statistically deterministic; hence, the mathematical cutoff of “statistical
signiﬁcance”. However, as Hunter has pointed out on many occasions, the
true object of science is to make true statements about the universe, and
thus to minimize error of all sorts. Krull and Paulson’s procedure obviates
this concern by entering both the lagged independent variables and the lags
of the dependent variable into the same regression equation, where they in
essence compete as predictors of the independent variable.

Thus, the analysis of the data gathered proceeded in four stages:

1) Data for each each of the variable clusters was gathered and

87

correlation matrices within clusters calculated. Cluster analysis via the
methods advocated by Hunter (1978) was used to reduce the data to those
items best representing the cluster as a whole, and the items aggregated for
form a single trendline.‘

2) Autocorrelations and partial autocorrelations were calculated for
lags up to 8 years for each of the aggregated trend lines. This allowed the
description of the each variable in question, albeit across the relatively short
term.

3) A matrix of cross-lagged correlations was in turn constructed
ﬁ'om the trend lines. The matrix of cross-lagged correlations was limited to
lags of 8 years due to the relatively small number of observations available
to draw from.

4) The matrix of cross-lagged correlations was used to select lags of
all variables for entry into the regression model. Two separate models were
formed, one predicting the public’s agenda and the second socioeconomic
outputs, in order to provide a test of the model presented as Figure 2. Also
included in the regression equations were values of the dependent measure
in previous years, as shown necessary by the analysis of partial
autocorrelations (years with signiﬁcant partial autocorrelations were
included in the analysis to “pre-whiten” the dependent measure, as above).
Durbin’s h, a statistic equivalent to the Durbin-Watson statistic but
designed for use in models containing lagged endogenous variables
(Ostrom, 1978), was observed, and in the case of a signiﬁcant Durbin-
Watson statistic, GLS estimation by the method of Instrumental Variables
(IV-GLS; Johnston, 1970) replaced OLS estimation.

The same procedure was followed in the two case studies as well,

 

“As will be seen, this led the analysis of the Policy Agenda to be split into separate
Administration and Congressional clusters.

88

except that the analysis of speciﬁc content areas obviated the necessity of
data reduction, and thus the cluster analysis stage was skipped for those
analyses.

Selection of the year as the unit of analysis is based largely on the fact
that many of the data are measured on a yearly basis. Ideally, in order to
permit numerous simultaneous estimations under GLS, time periods
should be as numerous as possible. Data on the media agenda, the policy
agenda, and liberalism itself are available accurate to at least plus or
minus one month, in principle making it possible to use the month or at
least the quarter the unit of analysis. Unfortunately, many of the other
variables, especially Crime Rate, Inﬂation Rate, and other social statistics,
are available no more ﬁequently than annually.

In addition, the choice of the year as the unit of analysis permits
removal of two potential problems with more accurate data. One of these
potential problems is seasonality within the data; for instance,
unemployment decreases annually during the winter quarter due to the
hiring of temporary help for the Christmas season. Additionally, as we
have seen in Chapter One, agenda issues take a period of months to build
up. Using the year as a unit of analysis will reduce sampling error by
reducing the random shocks on liberalism created by the short term
movement of agenda items, those movements that would NOT be described
as being caused by “rally” events.

Chapter Three
Results

In following the multi-tier approach laid out in the previous chapter,
discussion of the results obtained in the individual content areas will precede
the overall analysis. The last part of this section will be the analysis of the
speciﬁc content areas of Race and Ethnicity, Foreign Aﬁ‘airs.

Public Opinion

Figure 8 shows the result of cumulative annual net trend as calculated
for the purposes of this study, the function of this calculation being the
replication and extension of Smith’s original results (Smith, 1980, p. 496).
Comparison of the two ﬁgures shows a high degree of correspondence, the
most prominent differences being that the data in Figure 1 starts earlier and
ends earlier. Key relevant features, including the strong upturn in liberal
opinion starting in the early 1950’s, the acceleration which takes place round
1970, and the plateau around 1980, are as clearly shown in Figure 8 as in
Figure 1.

The additional data made available since the publication of Smith’s
paper also answers one of the key questions raised earlier: the early 1980’s
plateau proves to be short-lived; starting about 1984 the public’s agenda
resumes its liberal trend. Note the beginning of another plateau in the mid-
1990’s (although this is outside the scope of the present study).

Figure 9 graphs the average annual net trend against year.

89

 

 

 

 

m

amnesia-.-

2:9 3.24 53:26

 

 

Figure8

Cumulative Annual 'll'end

1940-1994

 

.02 ‘

.015 ‘

 

°°: H'.1i'45')'4€i g

 

 

3
0
til
i b
24 D
-.005-
«01‘
l
-.015 -.-r-.--1-4ﬁv
193019401950196019701$019mm

Year

Figure 9
Average Net Trend
1940-1994

92

Following the measurement procedure presented previously, positive scores
indicate liberal trends and negative scores conservative trends. Note that
the net is positive during 43 years and negative in only 10. The average
annual net trend was .4 points; with a standard deviation of .59 and a
standard error of .08, this differs signiﬁcantly from zero.

Analysis of the reduced set of trends within the nine content areas
retained yielded the correlation matrix presented as Table 9. Note that the
content area by content area n’s are somewhat inconsistent due to years
during which no active trends were present in one or the other content
area; these years were treated as missing data and excluded from the
individual correlation coefﬁcients.

Examination of the correlation matrix yields several interesting
ﬁndings. Opinion in the area of Civil Liberties is generally negatively
related to opinion in the other content areas, with the exception of that in
Foreign Affairs. This tendency was unexpected, and may indicate the
willingness of the public to accept intrusion into their civil liberties in order
to advance other worthy goals. (The positive relation between Civil Liberties
and Foreign Affairs is probably due to changes in opinion ﬁ'om the 1950’s
and 1960’s, as reductions in Cold War tensions led to the lifting of Cold War
era restrictions on the freedom of association.)

Feminism is associated with four issues other than Civil Liberties,
all positively. Opinions on Labor, Race and Ethnicity and Social Welfare all
seem reasonable to be associated with Feminism, but the highest
relationship, in fact, the highest on the entire table, is between Feminism
and Spending and Taxes. This could be explicable as some form of advocacy
for government intervention in Afﬁrmative Action if there was a similar

correlation between Race and Ethnicity and Spending and Taxes, but there

Area
CL
CR
ER
FA

LA
RE
ST
S W

93

Table 9
Overall analysis
Matrix of Correlations for Public Opinion

by Content Area

CL CR ER FA FE LA RE ST SW
1.000

.122 1.000

-.094 .446***1.000

.397" .290* .034 1.000

-.300**—.141 -.204 .131 1.000

-.065 .369" -.138 .040 .257”I 1.000

—.432**-.110 .085 .024 .309“ —.219 1.000

-.097 -.084 -.035 .015 .509‘".180 .127 1.000

-.035 .002 .341" .210 .265" .195 .207 -.166 1.000

*=p<.05
**=p<.01
***=p<.001

is not.

Cluster analysis of this correlation matrix led to the removal of Civil
Liberties from the cluster, due to its largely negative associations with the
other content areas, after it was veriﬁed that these relationships were not
the result of miscoding. All the other areas are signiﬁcantly and positively
related to at least one other content area, and removal of Civil Liberties
removes all the statistically signiﬁcant, negative results.

Average annual net trend data for the eight remaining content areas
was calculated (by summing the gross annual changes in each content
area and dividing by the number of trends active in that year) and subjected
to AR modeling. The results of this process are presented as Table 10.
(Note: In this and subsequent AR modeling of the other variable clusters
the autocorrelations and partial autocorrelations are presented up to lag 8.
This was to create the possibility of detecting trends associated with the
service of two-term presidents.) Clearly the Annual Net 'h'end data form a

simple, ﬁrst-order process.

Media Agenda

Before aggregation, inter-coder reliabilities were calculated for codes
assigned to articles within each content area and to the sample of articles
as a whole. These reliabilities are presented in Table 11. Although there is
no hard-and-fast rule concerning the evaluation of reliability, Krippendorf
(1980) suggests that items of reliability less than .67 be omitted, those in the
range of .67 to .80 be discussed only tentatively, and only those of .80 and
higher be used in the ordinary way. As will be seen on Table 11, all the
content areas show reliabilities in excess of .67, while Crime, Labor, and

Spending and Taxes fail to meet the higher standard.

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Table 10
Overall analysis
Autocorrelations and Partial Autocorrelations

Public Opinion

Partial
Autocorrelation Autocorrelation

.365" .365“
.012 -.132
.072 .136
.012 -.074
-.084 -.054
-.057 -.046
-.136 -.123
-.196 -.084

*=p<.05
**=p<.01
***=p<.001

%

Table 11
Intercoder Reliabilities on Media Agenda

By Content Area
Content Area Reliability
Civil Liberties .867
Crime .763
Economic Regulation .844
Foreign Affairs .807
Feminism .876
Labor .789
Race and Ethnicity .864
Spending and Taxes .734
Social Welfare .873

Overall .849

97

In most cases, however, the individual article is only one of multiple
indicators of prevailing media bias on a given topic within a given year. The
use of multiple (typically 5) indicators has the effect of increasing the
eﬂ‘ective reliability (Hunter, 1978), in this case to well above acceptable
levels.1 The overall reliability of .849 for all articles indicates that the coding
scheme as a whole was acceptable.

The matrix of correlations for the media agenda by content area is
presented as Table 12. Only two of the correlations are statistically
signiﬁcant, that between Civil Liberties and Foreign Affairs (-.349, p< .01)
and that between Labor and Feminism (.370, p<.01). The magnitude of these
two correlations is substantial enough to make it unlikely that they are the
result of Type II error; in fact, note also that these two pairs of content areas
were correlated within the public opinion data as well, although the
relationship between Civil Liberties and Foreign Affairs was positive for
public opinion.

Probably of greater consequence is the fact that the average
correlation on Table 12 is only .022, essentially (as well as effectively) zero. If
there exists a monolithic media agenda which shows systematic and overt
bias in one direction or another, substantial intercorrelation would have
resulted.

The lack of patterning in the correlation matrix made data reduction
by cluster analysis impractical (although several attempts were made). As
a result, the trend line for the media agenda was calculated by simply
summing the average for each content area for each year (no scaling was

necessary as they were measured on the same metric, average net

 

' In this case, using ﬁve items of reliability .734 (the lowest appearing on Table 11)
yields an overall scale reliability of .932 using the Spearman-Browne formula, nrx x/[(n-

1)rxx + 1].

Area
CL
CR
ER
FA
FE
LA
RE
ST
S W

%

Table 12

Overall analysis

Matrix of Correlations for Media Agenda,

by Content Area (N =47 )

CL CR

1.000

-.028 1.000
.217 -.061

-.349**-.020
.063 .089
.102 .030
.200 -. 172
.029 . 118

-. 139 -.073

ER

1.000

-. 140

.174

.088

-. 150

.042

FA FE LA RE ST SW
1.000

.150 1.000

.022 .370**1.000

.193 -.156 -.173 1.000

.125 .114 -.005 .134 1.000

.096 .122 -.073 -.034 -.199 1.000
*=p<.05
** =p< .01

*** = p < .001

t“
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99

Table 13
Overall analysis
Autocorrelations and Partial Autocorrelations

Media Agenda

Partial
Autocorrelation Autocorrelation
.266* 266*
.173 .110
.278* .226
-.194 -.354*
.074 .233
-.036 -.221
-.222 -.014
.066 125

*=p<.05
**=p<.01
***=p<.001

$833885

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1(1)

statements L or C). This trendline was autoregressed, yielding the
autocorrelations and partial autocorrelations presented in Table 13. Along
with a signiﬁcant, positive lag one partial autocorrelation, there is also a
signiﬁcant and negative lag four partial. The genesis of this is obscure,
although the four-year period suggests a correspondence to the presidential

election cycle.

PolicyAsenda

Scores for the congressional and administration agendas were
calculated and correlated on a content area by content area basis. The
correlations for the congressional agenda are presented in Table 14, and
those for the administration in Table 15.

Six of the 36 correlations on Table 14 are statistically signiﬁcant,
three of them involving the content area of Labor (with Civil Liberties,
Spending and Taxes, and Social Welfare). The ﬁrst is probably due to the
extensive debate surrounding the passage, and eventual repeal of the Taft-
Hartley act, which limited the rights of certain classiﬁcations of workers to
strike, and thus was seen as a Civil Liberties question by some. Feminism
in Congress is also related positively to action on Civil Liberties, as well as
to that on Social Welfare (the correlation between Feminism and Race and
Ethnicity, .235, is at the .05 < p < .06 level), which may indicate some sort of
conﬂuence of Great Society issues. Finally, Civil Liberties and Spending
and Taxes are signiﬁcantly and negatively related. This may be the result of
a historical coincidence between the Red Scare and balanced budget
attempts of the 1950’s.

Cluster analysis of the correlation matrix presented in Table 14 led to

the elimination of three of the content areas from the congressional agenda.

Area
CL
CR
ER
FA
FE
LA
RE
ST

SW

101

Table 14

Overall analysis

Matrix of Correlations for Congressional Agenda,

by Content Area (N = 46)

CL CR
1.000

.045 1.000
-.089 .093
.164 -.018
.243‘“ -.158
.362" .025
.140 -.032
-.290* -.212
.134 .199

ER

1.000

.211

-.040

. 195

-. 140

.023

.237

*

FA FE LA RE ST SW
1.000
.146 1.000
.008 .197 1.000
-.182 .235 .162 1.000
-.033 -.005 .259” .055 1.000
.236 .327* .334'“ -.013 -.005 1.000
* = p < .05
** = p < .01

**=p<.001

102

Table 15
Overall analysis
Matrix of Correlations for Administration Agenda,
by Content Area (N = 46)

Area CL CR ER FA FE LA RE ST S W

CL 1.000

CR .296” 1.000

ER .134 .063 1.000

FA .275” -.009 .026 1.000

FE -.034 .065 .004 -.175 1.000

LA .103 .000 .096 .087 -.128 1.000

RE .083 .089 .347**-.013 .128 .371**1.000

ST .189 .025 .204 .034 .058 .431" .442**1.000

SW .193 -.166 .418*’“.094 -.096 .597***.472**"‘.541***1.000
*=p<.05
** = p < .01

***=p<.001

103

The column sum for Spending and Taxes was negative, indicating either
that it was reverse coded or not part of the major cluster; once its coding
was veriﬁed it was eliminated. Similar, the column sums for Race and
Ethnicity and Crime were essentially zero, indicating that they were not
central to the the congressional agenda, at least along the Liberal-
Conservative dimension.

A trend line was constructed for the congressional agenda by taking
the sum of the score for each content area weighted by its factor score. The
results of the autoregressive analysis of this trend line is presented in Table
16. Along with the strong Lag 1 partial (indicating that the activities of the
previous year are a good predictor for any given year), there is also a
signiﬁcant Lag 4 partial, indicating a four year cycle in the data. This is
probably tied to the presidential election cycle; for instance, many presume
that legislative activity tends to be low during the election year (due to time
off for campaigning) and high in the year following the election (as new
programs are implemented).

Table 15 shows the correlations by content area for the administration
agenda are substantially stronger than those for the congressional agenda,
as might have been suspected given the nature of the two: the congressional
agenda must of necessity represent a degree of compromise in order to
create activity, while the administration’s agenda can be substantially more
monolithic. As a result, the average correlation in the matrix for the
administration agenda is almost twice that of the Congressional Agenda
(mean r = .146 vs. .078).

In the administration’s agenda Labor, Race and Ethnicity, Spending
and Taxes, and Social Welfare are all strongly interrelated, which seems
reasonable given the traditional appeal of the Democratic Party to groups

t"
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104

Table 16
Overall analysis
Autocorrelations and Partial Autocorrelations

Congressional Agenda

Partial
Autocorrelation Autocorrelation

.607*** .607***
.394" .039
.298“ .068
450*“ .364*
.416M -.025
.238 -.126

-.020 -.259
.079 .160

*=p<05
** = p < .01
*** = p < .001

{3638815

$88

105

such as organized labor and minorities and its attempts to aid these groups
via spending, and particularly spending on welfare. A Republican
administration would reasonably be expected to reverse all these areas.
Other signiﬁcant correlations include Economic Regulation with Race and
Ethnicity and Social Welfare, which again follows ﬁ'om the party-based
reasoning presented above. Civil Liberties is once again related to Foreign
Affairs, possibly for the reasons suggested above, and to Crime. This latter
may again be an artifact of the restrictions placed on the right of association
during the Red Scare years.

Cluster analysis eliminated Feminism and Crime from the
administration’s agenda. The former seems unlikely given the argument
concerning traditional party priorities made above, but it should be recalled
that there was only one Democratic administration within the scope of the
study which followed the advent of the Women’s Liberation movement, and
it was not strongly feminist in orientation due in large part to President
Carter’s religious (anti-abortion) beliefs. As a result, the column sum for
Feminism is negative, indicating that it is not part of the central cluster.
That for Crime is essentially zero; many of the administrations, both
Republican and Democratic, have attempted at various times to “get tough
on crime”, leading to a lack of variability in that content area.

As with the congressional agenda, the trend line for the
administration agenda was constructed ﬁ'om the sum of the individual
content areas weighted by factor score for each year. This trend, too, was
autoregressed, leading to the autocorrelations and partial autocorrelations
presented in Table 17. As with the other trends discussed so far, there was a
signiﬁcant lag 1 partial autocorrelation, indicating a year-to-year stability
of the agenda.

t"
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106

Table 17
Overall analysis
Autocorrelations and Partial Autocorrelations

Administration Agenda

Partial
Autocorrelation Autocorrelation

.518*** .518***
.418" .204

.314* .083

.201 -.053

.400” 346*

.316* .033

.208 -.106

.337* .241

*=p<ﬂ5
**=p<.01
***=p<.001

818836?”

88

107

More interesting is that the administration agenda does not show the
lag 4 cycle which appears in several of the other trends, but does show a
signiﬁcant 5 year cycle. The lack of a four-year cycle may possibly be
explained by the fact that there was only one President who served exactly
one four year term during the course of the study (Carter; the end of Bush’s
term fell outside the bounds of the study). A president reelected can be
expected to continue doing whatever it was he was doing in the previous
four years; thus, that aspect of the election cycle would be subsumed into
the lag 1 ﬁgures. Additionally, several of the presidents covered by the study
initiated their terms outside of the four year cycle ('II'uman, Johnson, and
Ford).

The existence of a lag 5 cycle is more problematic to explain.
Possibilities include: incomplete partialing due to Type II error; or the
activities of not the politicians at the head of the agenda but of the
professional managers who serve in the middle echelons of an
administration. Common management practice calls for medium term
planning cycles, typically ﬁve years in duration. This Lag 5 cycle might be
the manifestation of the results of these management planning cycles
percolating “to the top”, as it were.

Examining the pattern of correlations between Table 14 and 15
indicates that the two political agendas are not particularly strongly
associated. Only ﬁve of the nine content areas appear in both of their
associated trendlines. Further, the correlation between the two trendlines is
insigniﬁcant (r = -.199). This makes it unreasonable to combine the two into
a single policy agenda, and thus the administration agenda and the

congressional agenda will be maintained as separate agendas.

108

External SodoeconomicFactors

The matrix of correlations among the socioeconomic input variables
is presented as Table 18. The number of large correlations is noteworthy,
and suggests again that there is a substantial amount of trending in the
data. An obvious explanation for the substantial amount of intercorrelation
among these variables is simply that they are all chronologically trended to
a fairly large degree. Occupational segregation has been declining for both
blacks and women at various rates since the 1960’s; during that same time
period a “typical” unemployment rate has expanded from under 2% during
the war years to today’s 5-6% nationally.2 Income taxes, driven by
government expansion, have also tended to increase across that time
period, despite various short-term ﬂuctuations. Inﬂation, on the other
hand, tends to be less strongly trended because of its more dynamic nature,
leading to correlations which are less in magnitude; but it is still somewhat
trended as witnessed by a “typical” inﬂation rate of 1 1/2% during the
Eisenhower years versus 3-4% during Reagan’s second term.

More noteworthy, perhaps, is the pattern of signs in Table 18. The
economic indicators (with the exception of strikes) are negatively related to
the indicators of propinquity. Both conceptually and mathematically this is
the clearest possible indication of a two cluster structure. For this reason,
the economic variables were separated from the propinquity variables and
the two clusters maintained separately in further analysis.

The simplest explanation for the correlations between the number of
strikes and the other variables being negative is miscoding. (Conceptually,
of course, the number of strikes should remain with the economic variables
even though as originally coded they are positively related to the propinquity

variables.) Unlike the content-based variables discussed earlier, the coding

 

' National unemployment as announced on September 1, 1996: 5.6%.

109

Table 18
Overall analysis

Matrix of Correlations for Socioeconomic Inputs,

by Area
Integ Integ Income
Blacks Women Crime Infl Unemp Strikes Tax
Integratn
Blacks 1.000
Integratn
Women .726*** 1.000
Crime -.961*** -.746*** 1.000
Inflation -.499*** -.207 .410*** 1.000

Unemplmt -.568*** -.434** 576*" .100 1.000
Strikes 682*” .700*** -.693*** -.159 -.592”* 1.000

Income Tax-326*" -.692*** 956"" .358" 507‘" -.687*" 1.000

*=p<.05
**=p<.01
***=p<.001

110

of a larger number of strikes being evaluated as having a “liberal” valence
was hypothetical. For the purposes of data reduction by cluster analysis, the
number of strikes was reverse coded, as the magnitude of the correlations
involved strongly suggests that the number of strikes is related to the other
variables; in fact, the cluster analysis indicated that all the variables should
remain in one cluster or the other.

For the purposes of determining a trend-line for the economic
variables, a composite variable was constructed, consisting of the sum of
the standard scores for each of the economic input variable. This, too, is a
deviation from the procedures followed previously, which was necessitated
by the fact that unlike the various items making up the various agendas,
the variables mahng up the economic inputs were measured using
(sometimes grossly) different metrics. The use of mean—deviation removes
the considerations of scaling from these data. The propinquity variables,
being measured on the same metric (the 0 to 1 scale yielded by Duncan’s D),
were simply added.

Autoregression of the economic input variables leads to the
autocorrelations and partial autocorrelations presented in Table 19. The
pattern of substantial autocorrelations back to lag 8 (and clearly indicating
that it may continue into still longer lags) and the very high lag 1
autocorrelation indicates that, as suggested above, the data are strongly
trended across time. The same is true for the autocorrelations and partial
autocorrelations of the propinquity cluster, which is presented as Table 20.

Of particular interest is the presence of signiﬁcant higher-order
partials on both Tables 19 and 20, in particular, the signiﬁcant lag 8 partial
for each, negative in the case of the economic variables and positive in the

case of the propinquity variables. The partials for all variables were

1"
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111

Table 19
Overall analysis
Autocorrelations and Partial Autocorrelations

Socioeconomic Inputs - Economy

Partial
Autocorrelation Autocorrelation

966*" 966*“
.933*** . -.017
.909*** .124
.882*** -.049
854*“ -.023
834*" .120
829*" .118
.786*** -.409*

*=p<.05
**=p<.01
***=p<.001

l8

888888

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112

Table 20
Overall analysis

Autocorrelations and Partial Autocorrelations

Socioeconomic Inputs - Propinquity

Partial
Autocorrelation Autocorrelation

.979*** .979***
.960*** .037
.938*** -.079
.921*** .087
893*“ -.297*
.868*** -.043
.835*** -.276
.820*** .449“

*=p<.05
**=p<.01
***=p<.001

$8383

8

113

calculated out to lag 8 in search of potential political effects tied to the
presidential election cycle. It is important to recognize that although the
average presidential administration during the course of this study has
been substantially less than eight years, the possession of the White House
by one party or the other has proceeded on an almost perfect eight year cycle
until broken by the defeat of Carter in 1980, i.e. 1945-1952 Roosevelt/Truman,
1953-1960 Eisenhower, 1961-1968 Kennedy/Johnson, 1969-1976 Nixon/Ford.
The difference in signs is consistent with this: all of the presidents named
actively encouraged the civil rights movement’ to some degree at the
beginning of their administrations (hence a positive effect on propinquity),
but Democratic and Republican ﬁscal policies are diametrically opposed, at
least as deﬁned for the purposes of this study.

The propinquity data also show a signiﬁcant, negative ﬁve year lag.
As was brought out in the discussion of the autocorrelations of the
administration’s agenda, the genesis of a ﬁve year lag is somewhat
obscure; and it is unlikely that the two are related in that the ﬁve year cycle
in the administration’s agenda is positive and the ﬁve year lag in the
propinquity data is negative. If the two are related, it would indicate that
the ﬁve year programs hypothesized above intended to be liberal but actually
had the effect of reducing integration. This is not likely, but not outside the
realm of possibility.

The correlations between the socioeconomic output variables are also
presented, in Table 21, which poses much the same sort of analytical
problem as Table 18: one variable (union enrollments) is negatively related
to the other variables, and one (relative pay of women to men) shows little

apparent relationship to the other variables. The other three

 

’ It seems likely that this effect would have been magniﬁed if the data on female
workers had been removed from the propinquity cluster.

114

Table 21

Overall analysis

Matrix of Correlations for Socioeconomic Outputs,

Congrssnl
Blacks

Congrssnl
Women

United Way
Donations

Union
Enrollments

Relative
Pay (F/M)

Cong

Blacks

1.000

.795***

.523***

-.780***

-.095

by Area

Cong United Way

Women Donations
1.000
.319* 1.000
-.781*** -.384**
.041 -.482***
*=p<ﬂ5
** = p < .01

*** = p < .001

Union Relative
Erlmnts Pay
1.000
-.094 1.000

115

variables...election of blacks to Congress, election of women to Congress,
and donations to the United Way...are signiﬁcantly correlated, possibly
again because they are trended, albeit not as strongly as the input variables
are. (For instance, the number of women in Congress reaches a minimum
in the 1960’s, as opposed to the number of blacks, which expands
throughout the period of the study. Both reach maxima by 1990, however.)

As with the number of strikes in the analysis of socioeconomic
inputs, there is no compelling reason to maintain that union enrollments
was correctly coded with regard to valence; and the substantial magnitude
of the correlations between it and the other output measures suggest that it
should simply be reverse coded for the sake of cluster analysis. This cluster
analysis indicated that the relative pay variable was at best only weakly
related to other members of the cluster (if at all), and thus it was eliminated
from further analyses.

As with the socioeconomic inputs, and again for the reason of
removing inﬂuences created by the different metrics on which they were
measured, a composite variable for the socioeconomic outputs was created
by summing the standard scores of each of the remaining four variables on
an annual basis. Autocorrelations and partial autocorrelations for this
composite variable are presented Table 22. As with the socioeconomic
inputs, the results listed on Table 22, particularly the large but
systematically declining autocorrelation as lag increases, suggests strongly
trended data, in fact, even more strongly trended than was true of the
composite measure of the socioeconomic inputs.

Of particular interest is the signiﬁcant and negative lag 6 partial,
which indicates a six year periodicity in the data. This is completely
unanticipated by the data and discussion which preceded this analysis: it

1"
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QOU'IIFwNI-t

116

Table 22
Overall analysis
Autocorrelations and Partial Autocorrelations

Socioeconomic Outputs

Partial
Autocorrelation Autocorrelation

.988*** .988***
.973**"‘ -.132
.961*** -.150
.948*** -.048
929*" -.113
.901*** -.346*
872*" -.253
.841*** .164

*=p<.05
**=p<.01
***=p<.001

[883839

888

117

does not correspond to the four year election cycle, or the ﬁve year cycle
found in the administration’s agenda. It is not even quite half of the
fourteen-to-sixteen year cycle in ideological behavior observed by
Schlesinger (1939) and discussed above. In the absence of a coherent
explanation for this observation, the most that can be done is to account for

it in subsequent analyses.

Path analysis - overall model

To proceed with the path analysis of the overall model, the
correlations of the public agenda with the media, administration, and
congressional agendas, and the socioeconomic inputs (propinquity and
economic inputs) were calculated for lags of 1-8 years. These correlations
are presented as Table 23.

Although only the economic inputs are synchronously correlated
with the public agenda, examination of Table 23 reveals that each of the
variables is so correlated at one or more lag times. The media agenda is
signiﬁcantly correlated with public opinion ﬁve years later, the
congressional agenda and propinquity at lags of one to seven years,
economic inputs at lags of zero to six years, and the administration agenda
at lags of four and ﬁve years.

The spectral pattern

Irwzl < lrﬁdl < lrul > lrtrml > Iru+2|
is associated with the association of one variable with another at lag t-l
(Ostrom, 1978, Krull and Paulson, 1977). This pattern appears in several
places in the matrix, leading to the inclusion of the following variables in
the path model: public opinion at t-l (from Table 10); media agenda at t-4;
congressional agenda at t-2 and t-6; administration agenda at t—5;

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118

Table 23
Overall analysis
Legged Correlations with Public Opinion

Variable
Media Congressional Administration Propinquity Economic
Agenda Agenda Agenda Inputs
.130 -.108 .054 .227 -.288*
.055 -.320* -.037 .279* -.312*
.108 -.531*** .143 .342“ -.290*
-.043 -.361** .114 .328* -.291"‘
-.252 -.294* .360" .297 * -.368**
-.039 -.341** .448*** .278* -.325*
-. 134 -.444*** .220 .256* -.262*
-. 162 -.330* .211 264* -.100
-.002 -.233 .069 .178 -.028
* = p < .05
** = p < .01

**"‘ =p < .001

119

pr0pinquity at t-2; and economic enputs at t-4. The intercorrelation matrix
of these variables and public opinion at t-0 appears as Table 24.

Using the methods of Kenny (1979) and Blalock (1971), a path model
was constructed from the correlations in Table 24. This model showed that
the main predictors of public opinion at t-O were the congressional agenda
at t-2, the administration agenda at t-5, and public opinion at t-l. Residual
analysis, however, indicated that there was a signiﬁcant amount of
correlation between error terms: because of the presence of lagged
endogenous variables (public opinion at t-O and t-l), Durbin’s h was used
(Durbin, 1970; per Ostrom, 1978), yielding h=2.08, p<.01.

As pointed out in the previous chapter, this precludes use of OLS
estimation. Instead, again per Ostrom (1978), the amount of correlation
among errors was estimated by the Instrumental Variable-Generalized
Least Squares (IV-GLS) technique as in Johnston (1970). Using the
congressional agenda as an instrumental variable, the amount of
correlation between error terms was estimated (to be p=.595), and this
ﬁgure used to correct the original data for the correlation, as required by
the GLS technique. The corrected data yielded a corrected correlation
matrix, which appears as Table 25.

One consequence of the correction procedure is that many of the
correlations are smaller in magnitude in Table 25, when compared to Table
24. This is to be expected, as the uncorrected correlations include
components of both “true” relationship plus additionally a component of the
correlation among error terms.

More importantly, the correction of the correlation matrix has the
effect of removing public opinion at t-1 from the analysis: the corrected
correlations between it and the other variables range from -.134 to .187 (and

12)

Table 24
Overall analysis
Original Matrix of Correlations for Lagged Predictors

Public Public Congress Congress Propin- Economic Media
Agenda Agenda Agenda Agenda quity Inputs Agenda

w t-l t-2 w t—2 s4 t,4

Public
Agenda t-1 .384“
Congress
Agenda t-2 -.531*** -.320*
Congress

en t- -. -. .
Ag da 6 444'" 341* 450"
Propin-
quitytrZ .342* 279* -.586*** -.626***
Economic.
Inputst-4 -.368* -.291* .427" .606*** -.920***
Media

en a t- -. -. . . -. -,
Ag d 4 252* 043 292* 029 017 050
Administ.
Agenda t-5 .448" .360“ -.445** -.329* .576*** -.630*** .098

*=p<.05
**=p<.01
***=p<.001

Public
Agenda t-l

Congress
Agenda t-2

Congress
Agenda t-6

Propin-
quity t-2
Economic.
Inputs t-4

Media
Agenda t-4

Administ.
Agenda t-5

121

Table 25
Overall analysis
Matrix of Corrected Correlations for Lagged Predictors,

Public Public Congress Congress Pr0pin- Economic Media
Agenda Agenda Agenda Agenda quity Inputs Agenda

t—O t-l t-2 t-6 t-2 t-4 t-4
.029
-.406** -.078
-.283* -.065 .281*
.193 .104 -.311* -.379*
-.242 -.134 .146 .399* -.790***
-.235 .083 .273* -.008 .004 -.082
.339* .187 -.352* -. 193 .185 -.307* -. 130
* = p < .05
** = p < .01

*"‘* = p < .001

m

all are insigniﬁcant), and the sum of the correlations, .126, and average
correlation, .012, with the other variables suggest that the relationship
between public opinion at t- 1 and the other variables is largely due to
sampling error alone. Thus, public opinion (at t—1) was eliminated from the
analysis.

Subsequent path analysis yielded the path model presented as Figure
10. The direct causes of public opinion at t-0 are the administration’s
agenda at t-5 and the congress’ agenda at t-2. Under this model the other
variables correlated with public opinion are so because of their relationship
to these two variables. This model shows no signiﬁcant correlation among
error terms (Durbin-Watson d=2.217, p>.05). In accord with the methods of
Hunter (1977), the path coefﬁcients were used to “regenerate” a correlation
matrix (Table 26). Comparing this regenerated matrix to the original
matrix yields a residual matrix, which appears as Table 27. None of the
residuals are of sufﬁcient size to be statistically signiﬁcant, indicating that
there is no major misspeciﬁcation in this model, i.e. the model provides a
good ﬁt to the data.

The media agenda at t-4 in particular is both negatively and
indirectly related to public opinion, because of its effect on the congressional
agenda at t-2. This is particularly interesting in view of the facts that 1)
members of the House are elected on a biannual basis, and 2) Arnold (1990)
has shown that congressional candidates prepare themselves and run on
the issues of the previous campaign. This model suggests that two years
after the congress responds to the media, the people respond to the
congress, including by voting, leading to the sequence

123

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Figure 10

Overall Analysis -- Final Path Model

Public
Agenda t-l

Congress
Agenda t-2

Congress
Agenda t-6

Propin-
quity t-2
Economic.
Inputs t-4

Media
Agenda t-4

Administ.
Agenda t-5

124

Table 26
Overall analysis

Matrix of Reconstructed Correlations

Public Public Congress Congress Propin- Economic Media
Agenda Agenda Agenda Agenda quity Inputs Agenda
t-O t-l t-2 t-6 t-2 t-4 t-4

X

-.406* X

-.187 X .281*

.118 X -.122 -.325

-.150 X .112 .399“ -.790*

-.142 X .273“ .077 -.013 .017

.339* X -.138 -.172 .243 -.307* -.038

* = ﬁxed by speciﬁcation of model
X = variable eliminated from model

Public
Agenda t-1

Congress
Agenda t—2

Congress
Agenda t-6

Propin-
quity t-2
Economic.
Inputs t-4

Media
Agenda t-4

Administ.
Agenda t-5

125

Table 27
Overall analysis
Matrix of Residuals

Public Public Congress Congress Propin- Economic Media
Agenda Agenda Agenda Agenda quity Inputs Agenda

t-O t-l t-2 t-6 t-2 t4 t-4
X
.000* X
.096 X .000'“
-.075 X .189 .054
.092 X -.034 .000“ .000'“
.093 X .000“ .085 -.017 .098
.000* X .203 .032 .058 .000* .092

* = ﬁxed by speciﬁcation of model
X = variable eliminated from model

1%

Campaign 1: Media raises issue

Campaign 2 (two years later): Congressional candidates respond to issue
I
Campaign 3 (four years total): Public responds to candidates’ response.

The ﬁnding that the administration agenda at t-5 impacts public
opinion is also interesting in terms of the signiﬁcant ﬁve year partial
autocorrelation in the administration’s agenda. It, too, seems to imply the
existence of a ﬁve-year planning cycle.

The ﬁnal noteworthy element of this model is that, despite being
substantially correlated with public opinion, the model does not provide any
evidence of a causal relationship between either of the external
socioeconomic factors and public opinion. Rather, the model states that
those correlations are strictly due to the fact that public opinion and the
external factors are both caused by administration and congressional
action. In short, the relationship between the external factors and public
opinion “partials out.”

Impact on output variables

Analysis of the impact of the various agendas on socioeconomic
outputs was based on the desire, elucidated in the previous chapter, to
determine whether shifts in public opinion resolve themselves into overt
behavior. Toward that end, the analytic procedures used above were
repeated, this time in an attempt to create a causal model predicting
impacts on the outputs rather than public opinion, using public opinion as
one of the predictors.

With the univariate analyses already complete, the lagged
correlations of public opinion, the media, congressional, and

administrative agendas, propinquity, and the socioeconomic inputs with

127

the socioeconomic outputs were calculated. They are presented in Table 28.
Once again the spectral pattern described above is evident in several places,
and so the media agenda at t-4, the congressional agenda at t-6 and the
administration agenda at t-3 were used in the subsequent modeling
process. Several of the variables show their strongest association with the
output variables at the t-O (synchronous) time period (with correlations
declining afterward), and so the congressional agenda, propinquity, and
socioeconomic inputs at t-0 were included in the model.

Although none of the lagged correlations with public opinion were
statistically signiﬁcant, they also show the characteristic spectral pattern
centered around the t-2 lag. As the particular point of this analysis was to
examine the role of public opinion in predicting the composite
socioeconomic output variable, public opinion at lag t-2 was also included in
the analysis. Finally, after examining Table 22, autocorrelations of
socioeconomic outputs at t-1 and t-6 were included in the modeling process.

Inclusion of these variables in the modeling process led to the
intercorrelation matrix presented as Table 29. This correlation matrix was
subjected to path analysis in the manner described above, yielding the path
model attached as Figure 11.

The socioeconomic outputs at t-O variable was regressed onto the four
variables predicted by the models to have causal priority on it in order to test
for correlated errors, and a non-signiﬁcant test result was obtained (h = -
0.64, p > .05), suggesting that the assumptions of the model with regard to
error terms were not in jeopardy.

The predictions of this model lead to the regenerated correlation
matrix presented as Table 30. Subtracting the elements of Table 29 from

1"
so
an

QQGO'IAOONHO

- 128
Table 28
Overall analysis: Output model

Lagged Correlations with Socioeconomic Outputs

Variable

Media Congressional Administration Propinquity

Agenda Agenda Agenda
-.049 .564*** -.580*** 5331*"
-124 503*“ ”594*” -.800***
-.164 456""II -.611*** -.779***
n287* .411** a629*** a772***
“.348" .407" -.629*** -.765***
-.340** .408” -.606*** -.762***
‘5307* .440** a591*** .5759***
-.317* .391" -.599*** -.767***
-.247 .380“ -.600*** _.774***

* = p < .05
** = p < .01

**"‘ = p < .001

Economic
Inputs

.826***
.817***
.814***
.816***
.813***
.808***
.807***
.822***
.830***

Public
Agenda

-.196
-.202
-.228
-.202
-.185
-.125
-.071
-.130
-.173

129

Table 29
Overall analysis: Output model
Matrix of Correlations for Lagged Predictors

Soc-econ Soc-econ Soc-econ Cong Cong Admin Econ Public
Outputs Outputs Outputs Agenda Agenda Agenda Prop Inputs Agenda
t-O t-1 t-6 t-O t-6 t-3 t-0 t-0 t-2

Soc-econ
Outputs t—l .9ss*

Soc-econ

Outputst—G .970 .983'“

Cong

Agenda t-0 .564* .450 .553

Cong

Agenda t-6 .590 .568 .564* .238*

Administ.

Agenda t-3 -.629* -.621 -.610 -.286 .371

Propinq. t-0-.890 -.901 -.917" -.508 -.430 .560

Economic

Inputst-O .838 .848 .863 .478 .405 -.527 -.942*
Public

Agenda t—2 -.334 -.348 .345“ -.l96 -.166 .217 .325 -.306
Media

Agenda t-4 -.348* -.343 -.337 -.158 -.205 .219 .309 -.291 .117

* = ﬁxed by speciﬁcation of model

130

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8&5
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ﬂ -3
398 83.
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Figure 11

Overall Analysis: Output Model
Final Path Model

Soc-econ Soc-econ Soc-econ Cong

131

Table 30

Overall analysis: Output model

Matrix of Reconstructed Correlations

Cong Admin Econ

Public

Outputs Outputs Outputs Agenda Agenda Agenda Prop Inputs Agenda

t-0
Soc-econ
Outputst-l .988***
Soc-econ
Outputst-6 .901***
Cong

Agenda t-0 .564***

Cong
Agenda t-6 .440***

Administ.
Agenda t-3 -.629***
Propinq. t-0-.831***

Economic
Inputst-O .826***
Public

Agenda t—2 -.228

Media
Agenda t-4 -.348**

trl

.983***

.572***

.408"

-.611***

-.861***

.840***

-.203

-.287*

W W w as so w
.533***

.564*** .233
-.476***-.445*** .361"
-.917***-.586***-.592*** .576***

.s7o*** .500*** .661*** -.57s***-.942***

.345" .064 -.294"I -.037 .284"' -.320*
-.010 .073 .029 .213 .026 -. 112
* = p < .05
*"' = p < .01

***=p<.001

t-2

. 108

132

those of Table 30 leads to the residual matrix of the analysis, presented as
Table 31.

Unlike the other path analyses presented in this chapter, Table 31
contains several statistically signiﬁcant elements, indicating that the
model is misspeciﬁed in one or more locations. However, as Kenny (1979)
has pointed out, it is possible for a path model to be misspeciﬁed in certain
elements and yet correctly speciﬁed in others; that is, that because certain
parts of the model contain misspeciﬁcations does not necessarily invalidate
the rest of the model.‘ Since the part of the model of particular interest is
the impact of public opinion, if any, on the socioeconomic output variable,
and since the misspeciﬁcation does not include any of the combinations of
those variables, we can have conﬁdence that the relevant part of the model
is correctly speciﬁed.

The model presented in Figure 11 indicates that it is more likely that
public opinion is affected by the variables designated as socioeconomic
outputs than the reverse. Although that section of the model can be
constructed with a link from public opinion to outputs at t-O, such a
construction would not ﬁt the data as well as the model as presently
constructed. In addition, the link ﬁ'om opinion to output would be
statistically insigniﬁcant.

Sub-analysis: Foreign Affairs
Analysis of the causes of public opinion on the sub-area of Foreign
Aﬁ‘airs is simpliﬁed as compared to the overall analysis due to the lack of

measurable socioeconomic inputs and outputs. Propinquity could be

 

‘Indeed, this is one of the primary advantages of using Least Squares techniques
rather than the more efﬁcient Simultaneous Equations techniques, which distribute the
errors in parameter estimation created by local misspeciﬁcation across all the parameter
estimates.

t-0

Soc-econ
Outputs t-l .000*

Soc-econ
Outputs t-6 .006

Cong
Agenda t-0 .000*

Cong
Agenda t-6 .149

Administ.
Agenda t-3 .000“
Propinq. t-0-.058

Economic
Inputs t-0 .011

Public
Agenda t-2 -.116

Media

133

Table 31

Overall analysis: Output model

Matrix of Residuals

Soc-econ Soc-econ Soc-econ Cong Cong Admin Econ Public
Outputs Outputs Outputs Agenda Agenda Agenda Prop Inputs Agenda
t-1 t-6 t—0 ‘ t-6 t—3 t—0 t0 t2
.000*
-.122 .021
.160 .000* .000*
-.010 -.134 .159 -.010
-.040 .000“ .079 .162 -.017
.009 - 007 -.023 -.256T .052 .000*
-.146 .000* -.133 .127 .2531' .042 .014
-.056 -.3271’ -.231 -.234 .006 .2841' -.180 .009

Agenda t-4 .000*

* = ﬁxed by speciﬁcation of model

1' = statistically signiﬁcant residual

134

estimated using tourism and immigration ﬁgures, but these are only
estimates and are contaminated by many outside inﬂuences. Worldwide
economic input conditions are also poorly measured.I5 Outputs are also
problematic; indeed, it borders on illegal for private US citizens to engage in
foreign policy initiatives, prominent examples (Armand Hammer, Ross
Perot, Jane Fonda) nonwithstanding.

In the absence of external socioeconomic data, the basic model
(Figure 2) devolves to the four agenda areas: public, media, administration,

and congressional.

Univariate analyses

Autocorrelations and partial autocorrelations for the aggregate of the
public opinion items belonging to the content area of Foreign Affairs are
presented in Table 32. Few of the results are signiﬁcant; most notable is one
of the results that is not: public opinion on Foreign Affairs issues is not a
lag one process, indicating that it is fairly unstable from year to year, and
possesses little “momentum” of its own. The signiﬁcant lag 5 partial
autocorrelation indicates that the public opinion on Foreign Affairs does
possess a ﬁve year cycle. Unlike signiﬁcant ﬁve year lags in the
administration’s agenda, which are sensible in terms of rational planning
processes, the reason for this occurrence is unclear.

The autoregression analysis of the media agenda on Foreign Affairs
is presented in Table 33. This table shows results similar to those of Table
32: the only signiﬁcant partial autocorrelation is at lag 5 and negative,
again indicating a ﬁve year cycle, this time in the media’s agenda. It is

possible that these cycles have a similar genesis -- news reporters are also

 

“And in Marxist-Leninist nations, are subject to falsiﬁcation for the purpose of
serving revolutionary ideology (c.f. Heinlein, 1960/1980)

L“
no
on

QNIO>UIUFOONH

135
Table 32
Sub-Analysis: Foreign Affairs

Autocorrelations and Partial Autocorrelations

Public Opinion
Partial
Autocorrelation Autocorrelation
-.029 -.029
.191 .190
.208 .227
-.134 -.168
-.212 -.356**
050 .044
-.321* -.134
- 244 -.249
* = p < .05
** = p < .01

*** = p < .001

r‘
m
on

mQOECJ'IIhODNI-l

136
Table 33
Sub-Analysis: Foreign Affairs

Autocorrelations and Partial Autocorrelations

Media Agenda
Partial
Autocorrelation Autocorrelation
.030 .030
.128 .127
.135 .130
-.199 -.228
-.252* -.277*
-.129 -.100
-.336* -.254
.014 .084
*=p<05
** = p < .01

*** =p < .001

8883885

8

137

generally citizens of the nation in which they reside, and so this may be a
manifestation of the media’s opinions as citizens, so matching the public’s
opinion.

Table 34 contains the autoregressive analysis of the administration’s
agenda. As with the previous, there is apparently little stability in this,
although there is a signiﬁcant eight year cycle in the data. As pointed out
earlier, the terms of speciﬁc Presidents have rarely adhered to the four year
election cycle, but it is also worthwhile noting, as was done previously, that
party control of the White House has been following very closely to an eight
year cycle, to wit: Roosevelt/Human, 1944-1952; Eisenhower, 1952-1960;
Kennedy/Johnson, 1960-1968; Nixon/Ford, 1968-1976. The only exception to
the eight-eight pattern is Carter, who failed of reelection in 1980; but if one
assumes that Reagan serves one of Carter’s terms, the eight-eight pattern
continues to hold when Bush fails of reelection in 1992. Since the two parties
often pursue different foreign policies, and since they ﬂip-ﬂop in control, is
is possible that this eight year cycle represents control of the White House.

Finally, the autoregressive analysis of Congressional activity is
presented in Table 35. It is shown to be a lag one process, with activity in

one year predicted by the previous year’s activity.“

Path analysis - Foreign Amairs model

As with the overall model, the lagged correlations up to t-8 of the
media, administration and congressional agendas with public opinion
were calculated, and the results presented as Table 36. Although fewer of
the correlations are signiﬁcant (even in those three arenas alone) in Table

36 than in Table 23, they show the same spectral pattern, and so in the

 

' The partial of -.268 at lag 7 fails to be signiﬁcant due to the number of degrees of
freedom consumed by a seventh order partial.

r;
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0040:0145me

138

Table 34
Sub-Analysis: Foreign Affairs
Autocorrelations and Partial Autocorrelations

Administration Agenda

Partial
Autocorrelation Autocorrelation
.223 .223
.086 .038
.034 .007
.017 .006
.080 .077
.014 -.021
.026 .021
-.277* -.305*

I"=p<.05
**=p<.01
***=p<.001

88588

8

L"
m
on

00403015me

139
Table 35
Sub-Analysis: Foreign Affairs
Autocorrelations and Partial Autocorrelations

Congressional Agenda

Partial
Autocorrelation Autocorrelation
.359” .359“
.148 .022
.073 .016
.067 .038
.171 .152
.103 -.011
-.175 -.268
-.164 -.045

*=p<.05
**=p<.01

*** =p < .001

{858385

t

L"
no
on

QOCﬁnhODNl-‘O

140

Table 36
Sub-Analysis: Foreign Affairs

Lagged Correlations with Public Opinion

Variable
Media Congressional Administration
Agenda Agenda Agenda
-.087 -.042 -.086
-.170 -.188 -.207
.062 -.192 -.315*

-.132 -.127 -.172
-.104 -.087 -.297*
-.249* -.015 -.134
-.020 .037 .016
-.188 246* -.202
-.013 .251* -.024

* = p < .05

** = p < .01

*** = p < .001

141

same way the following variables were selected for construction of a path
model: media agenda at lag 5; congressional agenda at lag 8;
administration agenda at lags 2 and 4, and (from Table 32) public opinion at
lag 5. An intercorrelation matrix was calculated, and the results presented
as Table 37.

Path analysis of this correlation matrix started in the same way as
that performed for the overall analysis, by the methods cited above.
However, the test for correlated errors, in this case an estimate created by
adding the lagged residuals into the regression analysis (Ostrom, 1978)",
yielded insigniﬁcant results (t = .626, p > .05), indicating no signiﬁcant
correlation among error terms and obviating the need for IV-GLS
estimation. Hence, OLS estimation was used.

OLS estimation of the model led to the model shown as Figure 12. In
this model, changes in public opinion are created by the administration’s
activity both two and four years previously; in addition, the ﬁve year cycle in
public opinion continues. As in the overall model, the media’s agenda (four
years previously) contributes only indirectly, through its inﬂuence on the
the administration’s agenda at lag 2. (Also, as with the overall model, note
that the impact of the media’s agenda on public opinion is negative in sign.)
Finally, the media agenda at t-4 is shown to be in part created by (or a
response to) the congressional agenda four years previously.

As with the overall model, the path coefficients from this model were
used to create a “reconstructed” correlation matrix (Table 38) as a part of a '
test of the goodness of ﬁt of the model. The observed correlations were
subtracted from the regenerated correlations to create a matrix of
residuals, presented in Table 39. Residuals range from -.205 to .128; as with

 

’ Durbin’s h was calculated ﬁrst. Under certain conditions, however, the denominator
of the Durbin h statistic can be negative, yielding an imaginary b (that is, h would contain
the square root of -1). This was the case in this analysis, precluding the use of h.

Public
Agenda t-5

Administration
Agenda t-2

Administration
Agenda t-4

Media
Agenda t-5

Congressional
Agenda t-8

142

Table 37

Sub-Analysis: Foreign Affairs

Matrix of Correlations for Legged Predictors

Public

Agenda
t-0

-.231

a312*

-.297*

-.249*

.251*

Public Admin
Agenda Agenda
65 t-2

.005
-.059 .086
-.087 .398"
-.127 -.166
* = p < .05
** = p < .01

*** =p < .001

Admin Media
Agenda Agenda
t-4 t5
. 112
.011 -.367**

143

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Figure 12

Foreign Affairs Sub-analysis Final Path Model

144

Table 38
Sub-Analysis: Foreign Affairs

Matrix of Reconstructed Correlations

Public Public Admin Admin Media
Agenda Agenda Agenda Agenda Agenda
no t-5 t-2 t4 t5
Public
Agenda t-5 -.231*
Administration
Agenda t-2 -.312* .072
Administration
Agenda t-4 -.297* .069 .093
Media
Agenda t-5 -.124 .029 .398* .037
Congressional
Agenda t-8 .046 -.011 -.146 -.014 -.367*

* = ﬁxed by speciﬁcation of model

145
Table 39
Sub-Analysis: Foreign Affairs
Matrix of Residuals

Public Public Admin
Agenda Agenda Agenda
t-O t5 t-2
Public
Agenda t-5 .000*
Administration
Agenda t—2 .000* .067
Administration
Agenda t-4 .000* .128 .007
Media
Agenda t-5 .125 .116 .000*
Congressional
Agenda t-8 -.205 .116 .020

* = ﬁxed by speciﬁcation of model

Admin Media
Agenda Agenda
t-4 tr5

-.075
-.025 .000'“

146

the overall model, none of the correlations is signiﬁcant, suggesting that

the model is not grossly misspeciﬁced in any particular, and so provides a
good “ﬁt” to the data.

Sub-analysis: Race and Ethnicity

As with the overall analysis, the Race and Ethnicity sub-analysis
included not only public opinion and the media, congressional and
administrative agendas, but also external socioeconomic variables.
Propinquity was speciﬁcally measured for black workers as an input
variable; election of minority congressmen was used as output. As
discussed previously, propinquity is the simple idea that the more contact
people have, the more they like each other; this sort of contact can be readily

measured in the workplace in particular.

Univariate analysis

Contained in Table 40 is the autoregression analysis of the behavior of
aggregate public opinion on items classiﬁed in the content area of Race and
Ethnicity. The partial autocorrelations show that the data are strongly
trended, with a substantial Lag 1 autocorrelation, and smaller four and
seven year cycles. Again, the four year cycle may be associated with the
nation’s electoral cycle.

Unlike the public agenda data, there appears to be little or no trend in
the media agenda data, as shown in Table 41. None of the partial
autocorrelations are statistically signiﬁcant, although two (.262 at lag 5 and
-.267 at lag 6) approach it closely (t=1.63, df=41 at lag 5; t=1.62, df=40 at lag
6).

The administration’s agenda, like the public agenda, shows

t"
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an

ooqozcnuhcorcs-a

147
Table 40
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations

Public Opinion

Partial
Autocorrelation Autocorrelation
536*“ 536*“
.350" .102
.170 -.039
-.168 -.312*
-.184 -.017
-.320* -.197
-.509*** -.348*
-.291* .087

*=p<.05
**=p<.01
***=p<.001

{-1
m
N

mﬁwmtht-t

148

Table 41
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations
Media Agenda

Partial
Autocorrelation Autocorrelation
.053 .053
.060 .057
.094 .088
-.047 -.059
.260“ .262
-.206 -.267
-.142 -.128
.090 .107

*=p<.05
**=p<.01
***=p<.001

[883388

8

149

substantial year to year consistency, as demonstrated by by the large lag 1
autocorrelation in it on Table 42; there is also a signiﬁcant, positive lag 2
correlation as well. This is probably not unexpected; afﬁrmative action as
an issue has been a strong component of the agendas of Presidents
'Ituman, Eisenhower, Kennedy, Johnson, and Reagan; in general it was
necessary for each of them to repeatedly ask for the legislation they wanted
before it was passed by Congress.

Table 43 indicates that the year-to-year stability of the
administration’s agenda is not matched by congressional activity. The only
signiﬁcant partial autocorrelation is again the lag four partial, once again
suggesting that congressional activity in this area is tied to the Presidential
election cycle. The controversial nature of racial politics makes legislators
leery of election year activity; it seems more likely that activity takes place in
the second or third year of the cycle.

'Itends in occupational segregation (the overt measure used to
represent contact between the races, or propinquity) are by their nature
evolutionary in nature, with the consequence that it is strongly trended,
and this is clearly shown by the lag one autocorrelation of .979 in Table 44.
In addition, there is a substantial four year cycle in the data, and it is again
within reason to suggest that this is political in nature and tied to the
electoral cycle. There are signiﬁcant partials at lags 6 through 8.8

Similarly, the socioeconomic output variable, the election of black and
Hispanic congresspersons, as shown in Table 45, is also evolutionary in
nature, and thus also expected to be strongly trended. Further, as as
congresspeople serve multiyear terms, in 50% of the years (the election

year), the data should be identical to that of the previous year (that

 

' It is within the realm of possibility that they are the result of rounding error on the
higher order partials.

Lag

mQOQOIrFODNt-t

150

Table 42
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations

Administration Agenda

Partial
Autocorrelation Autocorrelation

.473*** .473***
.528*** .392"
.383“ .069
.415” .131
.432" .192
.341* -.020
.226 -.175
.310* .129

*=p<.05
**=p<.01
***=p<.001

8838':

88

r'
m
an

mQO>UII§ODNH

151

Table 43
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations

Congressional Agenda

Partial
Autocorrelation Autocorrelation
.168 .168
.161 .137
.222 184
.361“ .309*
.020 -.114
.243 .169
.090 -.072
.196 -.095

I"=p<.05
**=p<.01
***=p<.001

5:88:38”

83

152

Table 44
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations

Socioeconomic Inputs: Occupational Segregation by Race

Partial
Lag Autocorrelation Autocorrelation

1 .979*** .979”**

2 .963*** .110

3 .946*** 4.018

4 .907 *** -.545***

5 .876*** .059

6 .851*** .301*

7 .822*** 296*

8 816*” .654***

*=p<.05
**=p<.01
***=p<.001

£18

[88388

Lag

QN‘IQUIIGBCON

153
Table 45
Sub-Analysis: Race and Ethnicity
Autocorrelations and Partial Autocorrelations

Socioeconomic Outputs: Election of Black Congressmen

Partial
Autocorrelation Autocorrelation

.990*** .990***
.984*** .191
.969*** -.427**
.960*** .203
.941*** -.371*
927*" .051
.912*** .440“
.904*** .069

*=p<.05
**=p<.01
***=p<.001

88:88:

88

154

representing the ﬁrst year of the term for a representative). The pattern of
signiﬁcant partial every two years (lags 1, 3, 5, and 7) is probably a

consequence of the alternate year election sequence.

Path Analysis - Race and Ethnicity model

Again, the lagged correlations of the media, congressional, and
administrative agenda and the socioeconomic input (propinquity) with
public opinion on the topic of Race and Ethnicity were calculated. These are
presented as Table 46. As before, the table was examined for the
characteristic spectral pattern, which was revealed by several of the
variables at a number of lags. Selected for inclusion in the modeling
process were: media agenda (lag 6), administration agenda at lags 2 and 6,
and the economic inputs at lags 0 and 6.

None of the lags of the congressional agenda reached statistical
signiﬁcance. Again, the controversial nature of race relations tends to
preclude legislative activity with regard to them. For instance, one reason
why, as pointed out above, 'II'uman, Eisenhower, and Kennedy made
repeated requests for legislation was that the reforms they sought were
ﬁlibustered by the “Dixiecrats” — legislators from southern states. The
scoring system for congressional activity, based on legislation voted on, does
not reﬂect these activities.

The variables selected above were then correlated. The results are
presented as Table 47. Following this, in the same manner with the
previous models, the Race and Ethnicity data was path analyzed, leading to
the model presented as Figure 13. On the topic of Race and Ethnicity, public
opinion is found to be formed as a consequence of the activities of the

administration and the media. as well as the behavior of opinion in

t“
m
on

mQQCﬁIFODNt-‘O

155

Table 46
Sub-Analysis: Race and Ethnicity

Lagged Correlations with Public Opinion

Variable
Media Congressional Administration
Agenda Agenda Agenda

.025 -.152 254*
.098 -.120 .088
.107 -.146 .316*
.143 -.185 .156
.060 -.014 .044
.032 -.006 .235
.301* .202 .225
.088 -.046 .247*
.041 .186 .281*

*=p<05

** = p < .01

*** = p < .001

Economic
Inputs

.284*
.191
.125
.092
.204
.281*
.345“
.341"
.319*

Public
Agenda t-1

Public
Agenda t-4

Public
Agenda t-7

Administ.
Agenda t-2

Administ.
Agenda t-8

Media
Agenda t-6

Economic
Inputs t-0

Economic
Inputs t-6

156

Table 47

Sub-Analysis: Race and Ethnicity

Matrix of Correlations for Lagged Predictors,

Admin Admin Media Econ

Agenda Agenda Agenda Agenda Agenda Agenda Agenda Inputs

Public Public Public Public
to tr]. t-4 tr7
.347M
.157 .359"
-.476*** -.271 . 110
.397“ .103 .039 -.039
.281* .247 * .044 .088
.301* .032 .107 -.020
.292* .260* .356" .136
.231 .228 .250* .273*
* = p < .05
** = p < .01

*** = p < .001

t—2 t-8 t—6 W
.341**

.170 .010

.601*** .180 -.008

.707*** .593*** -.024 .746***

157

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Figure 13

Race and Ethnicity Sub-analysis Final Path Model

158

previous time periods. Although propinquity was correlated with the public
agenda at synchronous time periods, this correlation is shown to be
spurious.

Regressing the public agenda onto its immediate causes yields an
insigniﬁcant Durbin’s h (h=-.667, p>.05), indicating that error terms are
not signiﬁcantly correlated.

As with the previous models, the coefﬁcients in the Race and
Ethnicity model were used to create a regenerated correlation matrix (Table
48), from which was subtracted the original matrix, yielding the residual
matrix (Table 49). Residuals range from -.189 to .232, but none of them is
statistically signiﬁcant, indicating that the model is not grossly
misspeciﬁed in any of its particulars.

Comparison of Path Models

Prima facia, it seems clear that, apart from the constraint that they
attempt to provide some form of causal analysis of how public opinion
changes, the overall, foreign affairs, and race and ethnicity models differ
substantially. As noted above in their respective sections, one model
contained a problem with correlated error terms while the other two did
not; in two of the models the media agenda impacted public opinion
indirectly while in the third its impact was direct; the administration’s and
Congress’ agendas interact differently in each model; and so on.

To formally test the extent to which the models differ, Table 50 was
constructed. It consists differences in the lagged correlations of the media
agenda, administration agenda and congressional agenda9 with public
opinion between each of the models, calculated on a pair-wise basis (that is,

the overall model was compared to the foreign affairs model and then the

 

’ These three variables, of course, are the three which appear in all three of the models.

159

Table 48
Sub-Analysis: Race and Ethnicity

Matrix of Reconstructed Correlations

Public Public Public Public Admin Admin Media Econ
Agenda Agenda Agenda Agenda Agenda Agenda Agenda Inputs

t-O t-1 t-4 t-7 t-2 t-8 tr6 t-O
Public
Agenda t-l .347*
Public
Agenda t-4 .125 .359*
Public
Agenda t-7 -.476* -.186 -.067
Administ.
Agenda t-2 .397* .138 .049 .193
Administ.
Agenda t-8 .166 .058 .157 .162 .419
Media
Agenda t-6 .301* .104 .037 -.161 .119 .050
Economic
Inputs t-0 .254 .128 356* .204 .527 . 180* .013
Economic
Inputs t—6 .281 .097 .266 .273“ .7 07* .593* .084 .746*

* = ﬁxed by speciﬁcation of model

16)
Table 49
Sub-Analysis: Race and Ethnicity
Matrix of Residuals

Public Public Public Public Admin Admin Media Econ
Agenda Agenda Agenda Agenda Agenda Agenda Agenda Inputs

t-O t-l t-4 t-7 t-2 t-8 t-6 t-0
Public
Agenda t-l .000*
Public
Agenda t-4 -.032 .000*
Public
Agenda t-7 .000* .085 -.167
Administ.
Agenda t-2 .000* .035 .010 .232
Administ.
Agenda t-8 -.115 -.189 .113 .074 .078
Media
Agenda t-6 .000* .072 -.070 -.141 -.051 .040
Economic
Inputs t-O -.038 -. 132 .000* .068 -.074 .000* .021
Economic
Inputs tr6 .050 -.131 .016 .000* .000* .000* .108 .000*

* = ﬁxed by speciﬁcation of model

Lag

161

Table 50
Residual matrix

Comparison of path models

Overall vs. Overall vs. Foreign Affairs vs.
Foreign Affairs Race and Ethnicity Race and Ethnicity

Media Cong Admin Media Cong Admin Media Cong Admin
Agenda Agenda Agenda Agenda Agenda Agenda Agenda Agenda Agenda
.217 -.066 .140 .105 -.050 -.200 -. 112 .116 -.340**
.225 -.137 .170 -.043 -.200 -.125 -.268* -.063 -.295*
.046 -.339** .458*** .001 -.385** -.173 -.045 -.046 -.631***
.089 -.234 .286* -.186 -.176 -.042 -.275* .058 -.328*
-.148 -.207 .657*** -.312* -.280* .316* -.164 -.073 -.341**
.210 -.236** .582*** -.071 -.335* .213 -.281* -.009 -.369**

-.114 -.481*** .204 -.435***-.646***-.005 -.321** -.165 -.209
.026 -.576*** .413” -.250* -.376** -.036 -.276* .200 -.449***

.011 -.484*** .093 -.043 -.419*** -.212 -.054 .065 -.305*

*=p<.05
**=p<.01
***=p<.001

162

race and ethnicity model, and then the latter two models compared to each
other).

As Table 50 demonstrates, there are numerous signiﬁcant
differences between the data sets from which the models were constructed.
There are 27 correlations (lags 0 through 8 by three variables) in each of the
model-by-model comparisons: in each comparison at least 10 signiﬁcant
differences appear between data sets.” Only one signiﬁcant difference per
per comparison would be expected if the difference in the models was due to

chance alone.

Overall ﬁndings
As discussed in the ﬁrst chapter, the literature review preceding this
study and subsequent analyses led to the formulation of a number of

expectations, as enumerated on pages 52-53 .

1) The media will show a direct impact on public liberalism.

This expectation is not borne out in two of the three relevant models
constructed. Only in the Race and Ethnicity sub-analysis does the media
agenda have a direct impact on public opinion. In the other two models, the
media agenda instead demonstrates indirect...and negative in
sign...impacts on the public opinion via the mechanism of impacting on
one element or the other of the policy agenda.

2) The policy agenda will show a direct impact on public liberalism.

This expectation is borne out with the caveat that the notion of a
policy agenda has been demonstrated to be more complex than previously
formulated. In each of the three models one of either the congressional

‘° Overall vs. Foreign Affairs: 10 signiﬁcant differences; Overall vs. Race and
Ethnicity: 10 signiﬁcant differences; Foreign Affairs vs. Race and Ethnicity: 13
signiﬁcant differences.

163

agenda or the administration agenda has a direct impact on public opinion;
in the overall model both elements have such impacts. The only model in
which both elements of the policy agenda do not appear is the Race and
Ethnicity sub-analysis.

It is worthwhile noting that in the two models of which both the
administrative and the congressional agendas are a part, when the
consequence of one of those variables is positive in sign, the consequence of
the other is negative in sign.

3) The media will show a direct impact on the policy agenda.

As mentioned above, the media agenda’s impact on public opinion
works in two cases out of three through one element or the other of the
policy agenda. In the overall model, the media agenda directly impacts the
congressional agenda two years consequently (bearing out Arnold’s, 1990,
assertion); in the Foreign Affairs model the two year impact lag remains,
but the impact of the media is on the administration’s agenda.

In the Race and Ethnicity model, the media and the administration’s
agenda are only spuriously correlated.

4) The increase in public liberalism will be followed by an increase in
liberal activity in the nation.

This does not appear to be the case. In fact, the models suggest that
the socioeconomic input and output variables, as well as propinquity, have
little causal role, either as predictor or criterion, in the formation of public
opinion. In the only model in which the public agenda is shown to be
related to an external socioeconomic factor, it is the expected outputs which
impact the public agenda (in the overall outputs model). This is clearly
counterintuitive.

5) Separate models of the formation of public opinion will differ from

164

issue to issue.
This does appear to be the case. As pointed out above, on an issue-by-
issue basis substantially different models emerge from the analysis of the

same set of variables.

Chapter Four

Discussion

Evident in the nature and design of this study, although not explicit
until now, is that it is primarily exploratory in nature. As Rogers, Dearing
and Bregman (1993) imply, the question of “How...the media agenda, the
policy agenda, and the public agenda collaboratively inﬂuence each other, if
they do?” (pg. 79) has yet to be answered. This study was intended as a ﬁrst
step toward that end.

Ultimately, we conducted this project in order to consider three
questions, each of which is implied by considering the collaborative nature of
the various agendas. The three questions are speciﬁcally:

* How does public opinion change in the long run?

* What is the role of the nation’s media in this process?

* How does communication play a part in this process?

The ﬁrst two of these are addressed speciﬁcally by the design of the
study and the selection of its variables. The third is subsumed by, and a key
part of, the theoretical implications of this study.

Public Opinion Change

It seems fairly clear ﬁ'om Chapter One (see especially pp. 12-21) that
public opinion is fairly susceptible to inﬂuence in the short run, i.e. the
time period ranging from several minutes to several months. Mueller’ 8 (1970)
long-term study of Presidential popularity is one of the few which is

165

166

explicit in distinguishing effects which extinguish from those which do not
(the “rally” events).

The question of the long term is a very different question. There have
been very few studies which attempted to consider changes in public
opinion across periods of a decade or more. Again, Mueller pointed out a
general decline of Presidential popularity within the length of the
President’s term of ofﬁce, which he attributed to the alienation of groups
(an attribution he was unable to explicitly test); Davis (1975) was able to
parse certain long term effects (on the issue of social tolerance) into those
attributable to cohort changes in education and age and those which
transcended cohort changes (i.e., those which represented change in public
opinion within the population rather than across it), but made no attempt to
distinguish the causes of those changes which were consistent across
cohorts. For the most part, studies measuring media effects and opinion
changes across time periods of more than a few months - a semester at
most - are few and far between.

Examination of such long term eﬂ‘ects seems to call for the use of
long-term panel studies, and indeed, in the area of media violence several
have been conducted (e. g. Milavsky, Kessler, Stipp, and Rubens, 1982 ;
Leﬂrowitz, Eron, Walder and Huesmann, 1972). The long term panel study,
however, is subject to perils of its own, even apart from resources. These
include mortality and the question of external validity. Long term causal
modeling is a second possibility, but the ex post facto nature of causal
modeling requires a thorough discussion of the consequences of causal...or

pseudo-causal...statements made in that way.

167

Causation

When considering ex post facto the analysis of the impact of social
forces on a population, an immediate and vital consideration must be the
strength of the causal claims, and therefore the validity of the discovered
model, which can be made given the nature of this data. As Cook and
Campbell (1979) point out, the gain in external validity received by working
with “ﬁeld” data is offset to some degree by the loss in experimental control,
and thus internal validity. In terms of the “classic” canons of causation,
while this design gives us the possibility of establishing both concomitant
covariation and time ordering, it does not provide complete protection
against non-spuriousness.

As Granger (1969) mathematically points out, to have complete
conﬁdence in the causal impact of one of the variables measured as
proposed on another, one would require complete knowledge of the universe
of variables, although he goes on to point out that only all those of
appreciable impact themselves are truly necessary. Either of these
conditions is impossible to achieve.

Blalock (1971) refers to the results of path analysis as “causal
inferences,” pointing out that path coefficients can be potentially be biased
by unmeasured (and therefore uncontrolled) variables. It is one of the
functions of path analysis to distinguish relationships which are causal
from those which are spurious; in the absence of perfect measurement of
all relevant variables, path coefﬁcients and path models must be taken with
the proverbial grain of salt.

In the discussion which follows, use of the term “causes” or
imputations of “proof” of causality will be avoided; they are not warranted by
the techniques in use. The path coefﬁcients and models do, however,

168

provide evidence that causation may be occurring, and it is from this
assumption that discussion will proceed. The term “causal priority” will be

used in this regard, to suggest the evidential nature of the relationship.

Basic Findings

Given the caveat concerning causality discussed above, it is
important to note that in all three of the models...the overall analysis and
the two sub-analyses...long term changes in public Opinion are associated
with the activities of policymakers and the media. To the extent that we can
say it, the policy agenda and the media agenda have causal priority over
changes in public opinion.

It should be noticed that these changes are neither large in
magnitude nor immediate in occurrence. But in terms of magnitude they
are sufﬁcient to be detected by a study of no more than moderate power (see
below).

Further, there seems to be little question about the nature of the time
lag involved. As pointed out in Chapter Three, the substantial number of
even numbered lags present in the three models resulting from the three
analyses (vide Figures 10, 12, and 13) strongly suggests that the nature of
the inﬂuence is tied in some way to the congressional electoral cycle, as
suggested by Arnold (1990).

It is in the very nature of the American political system that
Americans focus most ﬁrmly on political issues during the time of the
election campaign. More importantly, the nature of the debate during that
campaign is generally retrospective: most of the members of House of
Representatives choose to defend their seats, and when they do so they are
forced to defend their records...and many times speciﬁcally to show that the

169

actions they have made during the course of their two-year term are
directly and speciﬁcally related to the positions they advocated during the
previous election cycle. Political debate not only occurs in two-year cycles
but also reﬂects back across the two year period to the previous cycle. This is
clearly demonstrated by the ﬁndings of this project.

Collaborative Inﬂuence

As Rogers and Dearing (1988) have pointed out, there is an extensive
literature that supporting the impacts of the media agenda and the policy
agenda on the public’s agenda, and, by extension, and to a lesser degree,
public opinion, and each other. The results of this study, in particular, those
associated with the ﬁrst three expectations support this literature, extend it
into the long term realm, and help to elucidate that interrelationship.

One particular element of the role of the policy agenda seems to be
recognition that the policy agenda does not appear to act as a unitary
construct. In both the overall model and the foreign aﬂ‘airs model, not only
do the congressional agenda and the administration agenda separately
impact public public opinion, they do so in different directions - when one
is positive in sign, the other is negative (see Figures 10 and 12).

Part of this is tied up, of course, in the nature of the measurement of
the two agendas: in an attempt to parse actual leadership from
acquiescence, events which were coded as part of one agenda were not
coded as part of the other and “contrary” events such as vetoes and
overrides were coded while “consonant” events such as signings and veto
sustainings were not. But certain of the results indicate that in some cases
the Congress speaks louder than the Presidency (in the overall model the
path coefﬁcient from Congress to public is larger than that of the

170

administration to public, although not signiﬁcantly so) and in others the
reverse is true (in the foreign affairs model the administration agenda
intervenes between Congress and the public, while the congressional
agenda does not appear in the Race and Ethnicity model at all.)

Equally interesting is the fact that the exact relationship between the
congressional and administrative agendas, and between those and the
media agenda, appears to be topic dependent. This was expected to some
extent due to the ad hoc nature of the issue network structure: diﬁ‘erent
issue networks use different paths to political inﬂuence (i.e. some enter via
the House, some via the media, and so on).

Preliminary speculation about the nature of the relationship between
the congressional, administration and media agenda can be developed
starting with the discussion (on page 154) of the lack of an inﬂuence due to
Congress on the sub-analysis of the Race and Ethnicity issue: it was then
presumed that that, while Administrations generally had strong views on
the subject, the Congress itself was split, and thereby forced into a relatively
subordinate position.

On the whole, across the three models it is the administration’s
agenda which most consistently shows direct effects on public opinion. This
follows logically in two ways: as pointed out previously (page 30),
administration policy tends to be somewhat more monolithic than
Congress’; and the administration, of course, possesses the “bully pulpit” of
the Presidency. There is no question that Congress can resist the will of a
President, but it is also clear that in the long run the administration is
more likely to have an eﬁ'ect on public opinion.

It is also fairly clear that, consistent with the ﬁndings of 'D'umbo
(1995), the greatest impact that the media agenda has on public opinion is

171

the impact it has on one element or the other of the policy agenda. Only in
the Race and Ethnicity analysis...again, that in which the congressional
agenda was stalled...did the media show a direct effect on public opinion,
and it is worth noting as well that it is only in the Race and Ethnicity sub-
analysis that the media’s relationship to public opinion is positive in sign.’l
(In that sub-analysis it is also at its largest in magnitude). This may
suggest, in a fairly preliminary way, that the media’s impact on opinion is
largest when working in a relative policy vacuum; that the policy agenda
normally speaks louder than the media agenda. This is consistent with the
model of biannual public discourse tied to the electoral cycle mentioned
above...people talk about what the candidates are saying, and much less
about what the media are saying.

Although not explicitly identiﬁed and tested as an expectation of this
study, the time series nature of this project, involving as many of 45 years
worth of data and the analysis of lags of up to eight one-year data periods,
suggests that long term impacts, reasonably measured in years, were to be
expected. This proved to be the case. Impacts on public opinion by other
agendas involved variables lagged a minimum of two years - none of the
synchronous variables were part of a relationship held to have causal
priority on public opinion.

Unexpected was the number of variables having causal precedence
on public opinion which affected it negatively. Most of the literature, save
almost solely for the results obtained by Trumbo (1995) and Page, Shapiro
and Dempsey (1987), suggests that a positive relationship exists, explicit in
Cohen’s statement about “telling the peeple what to think about.” This
again may be pointing up the difference between agenda setting and
changing public opinion, in that the former can be conceptualized as one

 

‘This is consistent with Pan and Kosicki (1996).

172

step in a process leading to the latter. By far the vast majority of studies
involve only agenda setting, and it seem perfectly reasonable that a positive
ability to set the agenda does not necessarily translate into a positive impact
on public opinion, if for no other reason than the mass audience may select
a different ﬁ'ame. Given the relative mistrust of both journalists and
politicians in the nation in recent years (McAneny, 1995’ ), the audience
may deliberately select a different frame. An issue network approach to the
dynamics of public opinion suggests a competing message environment,
and, by extension, a competing ﬁ'ame environment. The successful frame

need not be the one supplied by the media, the Congress, or the President.

Exta'nal Socioeconomic Factors

The failure of expectation four to be supported continues a recent
trend. Rogers, Dearing and Bregman (1993) implicitly reach the conclusion
that “real world” indicators do not play an important role in the agenda
setting process when they suggest that discovery of the reason why this does
not occur is one of the important questions for the ﬁrture of agenda setting '
research, despite evidence (c.f. Behr and Iyengar, 1985; Erbring,
Goldenberg and Miller, 1980; D’Alessio, 1992) that for highly obtrusive
issues “real world” indicators can be part of the process. (The study cited as
evidence, Danielian and Reese, 1989, uses drug deaths as its “real world”
indicator. In 1988, however, only 4865 deaths due to overdoses of both legal
and illegal drugs were reported in the US, according to the US Department
of Health and Human Services, 1991. Even if each of these had indirectly
affected 100 people in a consequential manner, drug deaths still would have
affected only a minute percentage of the population, and so cannot be

 

’ In reporting public Opinion of the honesty and ethical standards of 26 professions,
McAneny found that journalists ranked 11th, TV reporters and commentators 14th,
newspaper reporters 15th, Senators 22nd, and Congressmen 25th.

173

considered particularly obtrusive.)

It is counterintuitive to simply assume that external socioeconomic
factors play no role in the dynamics of public opinion. The absence of
support for this position shown herein is explicable in a number of ways:

* It is possible that it is true that external factors play an
unmeasurably small role in the dynamics of public opinion. The studies
cited above are all studies of the agenda setting process, and we have seen
previously, it is distinctly possible that agenda setting is only the ﬁrst of a
series of contingent processes which eventually lead to changes in public
opinion. It may be that external factors have ability to inﬂuence the public’s
agenda but have no impact on opinion due to the intervention of the framing
process. Framing, of course, permits the social construction of meaning
for “real world” events.

* Recent research by Kim and Hunter (1993a, 1993b) points out that
attitudes have a strong inﬂuence on behavior if the correct attitudes and
behaviors are measured; speciﬁcally, the relationship is strong if the
attitude in question is the attitude directly related to the behavior in
question.” When dealing with global measures of public opinion, it is
sometimes true that the opinion is directly related to the behavior in
question; for instance, one of the output variables was the number of
minorities elected to Congress, and one of the opinion items was “If your
party nominated a qualiﬁed (minority) for Congress, would you vote for
him?” However, the vast majority of opinion items were at best peripherally
related to the behaviors in question.

* It may be that the agenda setting effects cited above were too short

term to be of consequence in a study where the unit of analysis is the year.

 

‘ Price (1992) points out that opinions are derived from attitudes by means of making
the attitude explicit. The relationship between attitudes and opinions should be very high.

174

Behr and Iyengar, and Erbring, Goldenberg and Miller, were dealing with
effects which they expected immediately, while D’Alessio was dealing with
lags of up to two quarters (six months)

More importantly, it may be that many variables considered to be
obtrusive at the day-to-day level may not be as much so at the annual level.
Inﬂation, for instance, is held to be a highly obtrusive variable, because it
essentially aﬁ'ects the entire consuming population. In the absence of
catastrophic, crippling inﬂations of the sort which occurred only twice in
the course of the study (after World War 11 price controls were released, and
during the 1970’s gas 'crisis), the consequences of inﬂation are almost
invisible. The importance of inﬂation is what it does in the very long run, to
savings, pension plans, and the like, but on a day-to-day or week-to-week
basis its effects are subtle. In this case, the “long run” is a period of
decades, not one year to the next.

Demers, Craff, Choi, and Pessin (1989) have commented on the
difficulty of establishing what is obtrusive and what is not. The difﬁculty in
conceptualizing this variable can be seen when they deﬁne obtrusive in
terms of personal experience and then claim that drug abuse is obtrusive.
More advanced conceptualization, perhaps in terms of individual
consequence instead of simply experience, may be needed.

* It may be that the external socioeconomic variables were
misspeciﬁed. Some evidence of this appears in Figure 11, in which lagged
“output” variables are shown affecting opinion rather than vice versa. On
the other hand, the output variables were selected as outputs because of
their behavioral nature: voting, joining unions, donating money, and the
like.

* It may be that external socioeconomic factors do inﬂuence public

175

opinion, but do so at an effect size which too small to be detected in this
study. (A discussion of the power of the techniques employed appears
below.)

Role of Nation’s Media

As pointed out previously, the role of the media in changing public
opinion is both consistent and inconsistent from issue to issue. The media’s
agenda plays a signiﬁcant - statistically and substantively - role in each of
the three models which were evaluated. In two of them, the media’s
contribution to change in public opinion is indirect, via one or the other
elements of the policy agenda, and negative. In the third, the Race and
Ethnicity model, the impact of the media is positive in sign and direct. The
causes of this variation can only be speculated upon, as there is little about
any of the relevant theoretical positions that would predict this sort of
outcome.‘

Also interesting as the pattern of lags themselves. In each of the
overall model and the two submodels, as mentioned in the previous chapter,
the media play some role. The speciﬁc role varies from model to model, but
the media agenda is a part of each. More importantly, the all of the lag
times for media effects are even; in fact most of the signiﬁcant lags
involving the policy agenda items are even as well.

As brought out in chapter 3, Arnold (1990) has suggested that the
agenda for a congressional campaign is set by a large degree by the media

 

‘ One could speculate that Race-and-Ethnicity—oriented issue networks such as the
NAACP, in the absence of access to media via policymakers, attempted to frame their
issues directly through the media and were successful in doing so. Several of the key
images of the Civil Rights movement were intended as political demonstrations of unity
and power, but also possessed many of the characteristics of “pseudo-” or media events.
Most notable: Life magazine photos of a little black girl being escorted to class by National
Guardmen and Sheriff “Bull” Conner loosing the dogs and water cannon on marchers in
Birmingham.

176

coverage of the previous campaign in that district. This can perhaps be
seen most clearly in the overall model, where the media agenda at t—4
impacts directly on the congressional agenda at t-2; that is, two years later.
The number of even numbered lags involving the media and policy agenda
suggests that the inﬂuence of these on public opinion is tied to the two-year
congressional election cycle. An intuitive feel suggests that in the ﬁrst (non-
election) year people receive information about the performance of their
congresspeople but in the second that performance, as well as future plans,
are subject to actual debate, with the attendant attempted transmission of
priming and framing information.

Finally, it is worth noting that the media’s inﬂuence occurs
relatively far into the future. The media agenda appears in the various
models at lags from public opinion of 4-6 years, suggesting that it takes
some time for the media’s agenda to ﬁlter down to the public.

Explicit in the earlier chapters of this work was the idea that, for the
purposes of this work, the media’s agenda would be measured by, and
limited to, overtly biased statements by authors of works for periodicals.
Part of this limitation was due to the exigencies of measurement: as pointed
out on page 62, periodical works were considered to be the best possible
source through which to access the media’s agenda. And part of this
limitation is based on the nature of the role of the media in the political
process, which will be discussed in greater depth in the section about the
role of communication in the changing of public opinion, which appears

several pages subsequently.

177

Media Bias

In essence, although there does not appear to be a major theorist of
media bias, there seem to be three bodies of thought about its nature.

The ﬁrst of the approaches to media bias deals essentially with the
issue of gatekeeping: that writers and editors select from a body of potential
stories those which will be presented to the public and, by extension, also
select those stories of which the mass audience will hear nothing. This is
the level of analysis of White’s ( 1950) “Mr. Gates” study, in which the editor
selected among stories provided to him by his wire service, sometimes on
ideological grounds. As pointed out previously (pg. 45), it is the nature of
these ideological grounds which are of some concern.

Page and Shapiro (1982) provide an overview of the wide variety of
selection biases in the media. They include, among others, a nationalistic
bias, in which foreign news is “slanted” to provide news about US interests;
an anti-Communist bias; a procapitalist bias; a minimal government bias;
and a pro-incumbent bias in electoral news. This list is particularly
interesting in that most of these positions are associated with conservative
rather than liberal thought (through the long association of pro-business
interests and conservative thought; the media are, after all, businesses, at
least, in the US).

In an important sense, however, selection biases by themselves may
be essentially unknowable. If one considers the universe of all stories as a
population and a list of those which are covered as a sample, the
presumption is that, because the “sampling” procedure has the biases
outlined above built into it, the selection will therefore be biased. This is only
a presumption, however, as the population is not only unknowable but
unidentiﬁable. What would be “all the news of the world”? And, in the

178

absence of population data, while it is safe to presume that selection bias
occurs, it is impossible to know, or even estimate, its magnitude.‘5 There do
exist areas in which population data is available, such as major crime
events, but these are greatly outnumbered by those in which population
data is unavailable.

The second type of bias considered in the literature might be called
“coverage” bias. There is an extensive literature which attempts to codify
media bias by measuring the physical amount of coverage each side of some
issue receives (c.f. Stempel, 1969; Stempel and Windhauser, 1989; Stovall,
1985). This is typically measured in column inches for newspapers and
newsmagazines, although photographs (Batlin, 1954; Klein and Maccoby,
1954), and headlines (Stempel, 1965) have been counted (and measured) as
well, while analysis of television includes the amount of time devoted to
sides of the issue (c.f. Doll and Bradley, 1974).

The vast majority of these studies deal with the political realm
generally and the speciﬁc area of partisan politics. In a two-party electoral
system, it is reasonable to assume that half the coverage should be accorded
to one side and half to the other, and that therefore deviations from this
pattern are consistent with a coverage bias of some kind.

Reporting on issues on which there are more than two legitimate
positions (as was the case for several of the issues that compose this study)
starts to render the notion that there is an a priori “fair” distribution of
coverage untenable. Similarly, while two political parties roughly balanced
in appeal to the electorate can be considered reasonably as being an “issue”
with two sides which can be equitably reported by having equal coverage of

 

”Year to year changes in selection bias might yield relative ﬁgures, but it would be
unknown whether a year to year change would have been due to changes in the manner in
which the sample was selected, that is, changes in bias, or changes in the underlying
population.

179

both sides, many other social issues do not lend themselves to this sort of
artiﬁcial balance. An example from outside the scope of this study is again
the issue of abortion: while there are economic, social, and constitutional
arguments in favor of the “pro-choice” position, the “pro-life” position boils
down to the simple argument that abortion is immoral. What division of
coverage space between these very different types of argument constitutes
fair coverage? How far can the media deviate ﬁ'om this division and still be
“fair”? As with selection bias, it seems impossible to measure coverage bias
outside the electoral realm.

The third type of media bias to be considered herein is what might be
termed “statement” bias, that is, that members of the media can interject
their own opinions into coverage of an issue. This type of bias is of the sort
which engendered the ﬁrst concerns about media bias (c.f. Ephron, 1971),
and is the sort of bias which was discussed on pages 44-47, earlier.

Statement bias, unlike the other two forms, while subjective, is also
measurable to a degree in that the unit of analysis is knowable: a given
media event which contains equal numbers of statements biased in one
direction as those biased in the opposite can reasonably called “neutral”,
and one which contains no overtly biased statements can be called
“unbiased”. The discussion of pages 45-47 suggests that on the whole there
is a small but statistically signiﬁcant and measurable liberal bias at this
level.

Although the question of bias is in certain senses peripheral
(although not completely unconnected) to this study, given the perceived
importance of media bias in inﬂuencing the mass audience, it is
worthwhile to brieﬂy consider the results of the content analysis from
which we determined the media’s agenda. When the net score of biased

180

statements was aggregated across the entire database of articles, a mean of
+0.93 was calculated; that is, on the whole, across the entire database, there
was about one more liberal statement than conservative statement per
article. The complete distribution appears in the form of a histogram as
Figure 14.

As can be seen in Figure 14, the mode (at 297 articles) of the
distribution is zero; the diﬁering mode and mean (as well as the shape of
the distribution itself) indicates a certain degree of skew. More importantly,
the “spike”-like shape of the distribution suggests not a normal (or bell
curve) distribution, but instead but instead a highly narrow distribution
typical of skilled practitioners attempting to hit a goal.”

The standard deviation of this distribution is 2.34, and the mean
therefore differs signiﬁcantly from zero (t=17.63, p<.001). Although the
range is 37 points across the entire distribution, the standard deviation
suggests that a nine point scale would be sufﬁcient" to capture 99% of the
variation in this distribution.

The discussion concerning the nature of the Liberalism scale points
out that there may be an element of measurement error in the estimates of
liberalism, as the Conservative end of the scale was derived by essentially
reversing the Liberal items. As pointed out at that time, this fails to capture
the extent to which the scale is not essentially bipolar, and speciﬁcally fails
to account for those issues and ideas which are central to conservatism but
peripheral to liberalism. In short, the ﬁnding of a liberal bias across the
entire sample may simply be the result of measurement error.

It is also worth noting that the mean bias of +0.93...less than a single

 

'Kurtosis = 15.3, indicating that the distribution is substantially narrower than normal
(the kurtosis of a normal distribution is 0; Nie, Hull, Jenkins, Steinbrenner, and Bent,
1975).

7 2.34 x 2 tails x 1.96 (the 99th percentile) = 9.17

181

 

 

 

 

w).
my
m1
200‘ ‘
215°: .
100‘ O
. .0 .
501 '
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.5(; r g , T , 1 -
.20 .15 -1o -5 o 5 10
Score
Figure 14
Frequency Distribution of Net

Liberal-Conservative Statement per Article

182

point...on a nine-point scale is roughly consistent with the other studies of
the subject, as discussed in pages 44-47. That is, again, a small but
statistically signiﬁcant and measurable liberal bias has been detected.

Also revealed is that the sample indicates that there is indeed a
competing messages environment, as is necessary to the theoretical
positions articulated by Zaller (1992) and Tapper (1995). Along with the 297
studies which showed no net bias, 492 were coded as having a net
conservative bias. Further, it is important to recognize that these are net
scores: the proportion of articles which were coded as possessing no biased
statements at all was fairly small (9.9%), while 62.5% of articles contained
statements which were coded as liberal simultaneously with statements
coded as conservative.

Direct evidence of a competing messages environment is not
consistent with the popular view of a monolithic, systemic entity called “the
media” which is unrelentingly liberal in orientation. Neither is the lack of
issue-by-issue consistency of media messages, as was demonstrated by the
lack of correlation between issues in Table 12. If a persistent, systematic
liberal bias does occur, it must do so at a level higher level of abstraction
than that of the statement.

Finally, there is the question of “What inﬂuences the media?” Only in
the Foreign Affairs sub-analysis does causal modeling indicate that other
elements of other agendas have any causal priority on the media’s agenda.
In Figures 10, 11, and 13, the media agenda acts as an exogenous variable.

This is particularly interesting in that the various external
socioeconomic factors are as unrelated to the media agenda as they are on
public opinion or the other agendas. Although, as was made clear above,

the media agenda as measured herein consisted of statements of an overtly

183

biased nature, one would presume that “biased” reporters would seize on

events for the opportunity to make their points.

Communication generalb'

Finally, apart ﬁ'om the overt contributions to the debate on issues
provided by members of the media, there is the question of what other roles
does communication play in the change of public opinion. This in turn can
be subdivided into questions regarding two diﬁ'erent types of
communication: interpersonal and mediated.

Interpersonal communication was not measured or considered as
part of this project, yet it is presumed to play several parts. It was assumed
that interpersonal communication is part of the process of the development
of interest networks; speciﬁcally, as issue networks are assumed to start at
the local level, it must be interpersonal communication which brings the
original members together. Further, as McCombs and Shaw (1972) point
out, evidence indicates that knowledge of the speciﬁc consumption of
mediated messages does not predict agenda setting eﬁ'ects as well as the
assumption of a message “milieu”. It is known that mediated messages
provide topics for subsequent conversation, and Zhu, Watt, Snyder, Yan,
and Jiang’s (1993) results suggest that talk is as much a part of the milieu
as television.

More saliently, separating the media agenda and the policy agenda
into separate components of the analysis begs the question of how the policy
agenda is to be communicated. Legislation qua legislation can have no
direct impact on public opinion; there has yet to be a law passed which
mandates speciﬁc responses to opinion items. Legislation, whether
engendered by the Congress or the administration, can have a direct effect

184

on external socioeconomic factors, and indeed has been designed on
occasion to inﬂuence them. But considering the impact of the policy agenda
on the public’s agenda or on public opinion presupposes that that activities
of Congress and the administration are communicated to the people in
some way, and our understanding of the mass audience that composes the
“public” in “public opinion” requires that they be communicated in large
part by mediated messages.

The leads in turn to the next question: at what point do mediated
messages become the media’s messages? Patterson (1993) provides an
illuminating example:

“...Mondale loses the New Hampshire primary to Gary Hart, 41 to 29
percent. A desperate Mondale borrows an advertising line ﬁ'om Wendy’s
hamburgers to ask of Hart: ‘Where’s the beef?’ Reporters pick up the line
even though Hart has provided them with a score of detailed, innovative
position papers. The press concludes that Mondale is back in the thick the
race after primary wins in Georgia and Alabama, despite losses in six
other states on the same day.” (pg. 40)

In the terms used herein, Mondale successfully reframed’ the issue
of who the Presidential candidate should be into his own terms. This
reframing was conducted via the media. Patterson makes it clear that in
his opinion at least this reframing was unwarranted.

This situation makes a classic discussion item: speciﬁcally, what
was the media to do? The frame was supplied by Mondale. To fail to report
it, while continuing to report on Hart, would have constituted bias (selection

 

‘ More speciﬁcally, he set the agenda by making stances on the issues the most salient
factor in selecting a Presidential candidate (rather than, say, personal magnetism),
primed the issue by claiming that a candidate should be evaluated by the substance of their
positions on the issues, and then framed it by claiming that Hart’s positions were
insubstantial.

185

bias). 'lb report it with the additional information about the position papers
juxtaposed would have been, in essence, to call Mondale a liar.

J uxtaposition, that is, the placement of images in combinations
which create meaning (Eisenstein, 1942/1975), gives visual media the ability
to create, deliberately or inadvertently, and communicate frames (c.f. Lang
and Lang, 1974). Similar phenomena attend the print media, and for much
the same reason: no medium can exactly reproduce all the information
contained in an event, and thus salient elements have to be selected for
transmission...and the judgment of salience is necessarily given to the
communication channel rather than to the source or receiver.

The results of this study indicate that, despite the role of the media in
conveying the policy agenda, there is a point at which the media agenda
and the policy agenda can be separated. Clearly, writers or reporters who
use their medium to make an overtly biased statement of opinion can be
seen to be the source of that particular message. Similarly, policy makers
(or would-be policy makers) who produce their own materials - their own
newsletters, newspapers, TV and radio shows - and who exercise creative
control over their own materials can be seen as the sources of those
materials. But it remains to be determined where in the middle ground in
between that public opinion impacts created by media coverage of policy
issues are the responsibility of the policy makers and when they are the

responsibility of mass communicators.

Caveats
In virtually every scientiﬁc study there is the necessity that the
potential problems of the study be considered, at least in passing, as such

consideration will aid the scientiﬁc community in evaluating the “weight”

186

to apply to the results. A study such as this which attempts to explore a
topic at a broad, systemic level for a long period of years by necessity makes
a number of assumptions about which elements are to be included and
which to be excluded. In addition, there are a number of assumptions about
the appropriate way to operationalize broad, systemic variables, and once
the operationalizations have been made, to analyze the interrelationships
between those variables.

For the most part, the previous chapters have been explicit about
what assumptions have been made and why those assumptions were made,
and to reiterate those here would be both redundant and tiresome. There
are two additional areas, however, to which additional consideration need
be paid before this work can said to be complete. These are theoretical
considerations and the calculation of statistical power.

Theoretical consideration

Two theoretical formulations have played a part in this study, the
formulation of agenda setting as the ﬁrst in a series of processes which
together lead to changes in public opinion and the issue network approach.
This study was not a formal test of either theory; rather, these theoretical
positions are presented as attempts to organize and to make clear the
connection between seeming disparate processes and bodies of scientiﬁc
literature.

A perspective which holds, as presented on pages 24-25, that agenda
setting, in conjunction with priming and framing effects, has the potential
to inﬂuence public opinion seems to be clearly where Iyengar (Iyengar and
Simon, 1993) is headed. Further, it would view agenda setting and the

dynamics of public opinion as related rather than separate phenomena,

187

drawing together the extensive body of literature devoted to each. Such an
approach is consistent with Cohen’s (1963) summation of the two ﬁelds —
“(The press) may not be successful much of the time in telling people what
to think, but it is stunningly successful in telling its readers what to think
about...” (pg. 13) - in that, as the ﬁrst step in a multi-step process, the
achievement of agenda setting effects would be substantially easier than
changing opinion, the last step in that process. Further, the intervening
steps, priming and framing, would seem to be fairly difﬁcult, particularly
in the face of selectivity processes and a competing messages environment.
If this perspective is accurate, it is perfectly consistent for the media to have
substantial short term effect on the public’s agenda and only modest effects
on public opinion in the long run.

The issue network approach was devised to provide an explanation
(or, more speciﬁcally, a rationale) for including both the media agenda and
the policy agenda in a study on the dynamics of public opinion. As Rogers
and Dearing (1988) point out, these are two separate research traditions,
and typically studied in isolation by different groups of scholars. In the
absence of a reason to combine them, one runs the risk of comparing apples
to oranges.

Yet the issue network approach not only suggests that the media
agenda and the policy agenda are in some ways alike (because of their
ability to access the mass audience), it also points to yet a third sociological
grouping whose effects should be similar: celebrities. It is possible to name
a number of celebrities, who, by reason of their celebrity have access to
media time, and are willing to use it to advance causes in which they
believe; that is, to advance the causes of issue networks of which they are

members or supporters.

188

Consideration of the notion that celebrities could also inﬂuence public
opinion in a manner similar to that of media members and policy makers,
that is, by using their access to the media in order to communicate
preferred ﬂames on an issue, has already been suggested by Mankiewicz
(1989; although many of the celebrities Mankiewicz names are media
members themselves, again leading to the question of where the line
between the media agenda and the celebrity agenda will be drawn).
Further, the substantial literature (and continued use of) celebrity
endorsers in advertising suggests that there may be a connection between
celebrity endorsement and public opinion, at least on the issue of product
purchase. Thus, an issue network approach has the potential to unite these
three different literatures, and is thus worthy of future consideration, at

least on the grounds of parsimony.

wau'

The question of statistical power is actually one half of a broader
question, and that is the question of testing error. Type I error, the error of
the false positive, arises from the necessity of sampling, and can be
minimized by the establishment of a stringent alpha value (Lin, 1976). Type
II error, the error of the false negative, arises in part from positivist
requirements of parsimony.

Power is the logical inverse of the probability of Type 11 error; in
short, is is the ability of a statistical test to detect true relationships in a set
of data. Power is a function of the effect size of the true relationship, the
alpha level, and the number of cases in the relationship being tested
(Cohen, 1988).

N’s for this study vary, as the tables in Chapter Three show. This

189

occurs for a variety of reasons: the availability of data, in terms of what
epochs it is gathered and published; missing data within an epoch; and the
number of data points within the epoch. A study using annual data of the
time period from 1945-1990 starts with a set of 46 data points. In some cases,
for instance, in the measurement of public opinion, cases could be added at
the beginning, and thus those analyses which deal only with public opinion
have more cases than others. On the other hand, there was an amount of
missing data from some of the external socioeconomic factors, most notably
pr0pinquity, and thus those analyses may have a small number fewer
cases. From the overall standpoint, it needs to be pointed out that 46 cases is
not a particularly large number for a time series analysis.

Nothing in the literature review led to the suggestion of negatively
signed impacts. Consequently, one-tailed tests of statistical signiﬁcance
were used. This is important in that, although neither Lin (1976) nor Cohen
(1988) recommend this, establishment of alpha level was perhaps the only
means available to control both Type I and Type II error.

Cohen (1988) suggests that effect sizes be considered as falling into
three basic categories: small (r = .10), medium (r = .30), and large (r = .50).
There was no expectation that this design would be suitable for the detection
of small effects: the critical r for 46 cases using the one-tailed test is .246;
power would be a mere .16, that is, there would be basically ﬁve chances out
of six that this relationship would not be detected. On the other hand, large
effects are readily detectable using 46 cases, yielding a power of about .98
(leaving only 2% chance of Type II error for relationships of this
magnitude).

The question of the medium effect size is the key question in

establishing alpha, from the point of view of this study. As Cohen (1988)

190

points out, .3 is a fairly typical correlation in the social sciences.

Continuing to use the one-tailed test after the detection of negatively signed
results — as was done — increases the possibility of Type I error from .05 to
.10; however, it also increases the power of the test for relationship of
medium effect size ﬁom .54 for the two-tailed test to .66 for the one-tailed. In
other words, the .05 loss in protection against Type I error was offset by a .12
gain in protection against Type II error.

Potential problems with Type I error are minimized in the path
analyses, as an isolated spurious relationship would lead to increased
speciﬁcation error in the model (as each path refers not to a single
correlation but instead a consistent pattern of correlations). However, the
likelihood of Me 11 error is substantially higher than that of Type I error,
and it is possible that part of the reason that the three models (Overall,
Foreign Affairs, and Race and Ethnicity) differ is Type II error.

Concludingnote

It seems at times that each scientiﬁc study ends with a call for more
research in the area of study, and this shall be no exception. The
overarching justiﬁcation for this research was that it would start to
explicate the long term interrelationship between public opinion, the policy
and media agendas, and external socioeconomic factors. Several of the
expectations (based on the existing literature) were supported and others
were not; in some cases the interrelationships were more complex than
expected.

One area in need of further explication is the nature of the
relationship between agenda setting, priming and ﬁ'aming. As mentioned
previously, there is a modicum of evidence suggesting that the three

191

processes are both related and contingent stages in the overarching process
of mass opinion change. This is consistent with recent theory (c.f. Chaiken,
1980; Petty and Cacioppo, 1984) on the nature of persuasion, which holds, in
essence, that involvement with an argument is a necessary precursor to
actual persuasion, as opposed to compliance.

This phenomenon could be studied under laboratory conditions using
a methodology similar to that employed by Iyengar and Kinder (1987),
utilizing mock newscasts. Field experimentation would be more complex,
but could be accomplished given inside information involving a “breaking”
story, or as part of the quadrennial Presidential primary campaigns: the
researcher would have to have pre-primary opinion data on prominent
candidates, and then would need to analyze candidate statements
searching for attempts to set the agenda, and prime and frame issues;
would need to analyze media content to see which of these attempts were
transmitted; and would need to gather running data on issue salience and
opinion in the affected audience.9

A second area which suggests itself for further empirical
investigation is that of the question of obtrusiveness. As mentioned
previously, it may be that in the long term there are no truly obtrusive
circumstances. But this depends in large part in the conceptualization of
“obtrusive”. Certainly there are socioeconomic factors which affect
everyone, but for the most part, and in the long run, the effect of these
factors is fairly small. Examples include issues such as inﬂation,
education policy, and the Cold War: each affects every US citizen, but across
a period of years the total effect is fairly small. It may prove that the only

 

”The 2000 Republican campaign for the nomination might be highly suitable for
analysis, and any primary campaign conducted by the party out of ofﬁce should provide
good grounds for data gathering. (The party in ofﬁce generally has fewer problems
arriving at a candidate.)

192

truly obtrusive issue, at least from the viewpoint of a period of years, is war.

War, course, affects every member of a society eventually, and can do
so drastically. During the era of modern public opinion polling there have
been three major, long term wars, World War 11, Korea, and Vietnam, and
it should be possible to examine the relationship between public opinion and
the actual events of those wars using techniques such as employed herein,
or by 'IYumbo (1995).

Another approach to examining the question of obtrusiveness would
be to approach the subject from the standpoint of meta-analysis (Hunter,
Schmidt, and Jackson, 1982). Once a formal, consistent operational
deﬁnition of obtrusiveness is developed, it could be applied to extant studies
of the issue. Studies could be classiﬁed as “Low” and “High” in
obtrusiveness, accumulated, and effect sizes between the groups compared,
with the expectation that the effect size of the high obtrusiveness group
would be higher than that in the low obtrusiveness group.

A third area ripe for further investigation is that of the development
and inﬂuence of the issue network. Numerous writers, including
Baumgartner and Jones (1993) and Zaller (1992), stipulate the existence of
groups whose actions inﬂuence policy and opinion, frequently terming
them “policy elites”. But the actual development and motivation of the issue
network is assumed, or undiscussed and unexplored.

An in-depth examination of an issue network would call for the use
of historical techniques. An issue, such as the recent passing and signing
of the Communication Decency Act, is suited to such an investigation. The
policy debate took place publicly on the floor of the Senate and in the full
view of the public. The debaters, US Senators, are identiﬁable not only as to
identity but also as to prior association — both ideological and ﬁnancial —

193

with a variety of extant issue networks, whose stands on the legislation can
be determined as well from their statements on the issues. In short, it
should be possible to trace a “chain of inﬂuence” backward from the event to
issue networks which invented it...if they did.

The nature of the liberal shift itself is a matter of some concern to the
communication researcher, in that different sources of the shift support
different theoretical models of opinion change. Consistent shifts of the sort
shown in Figures 1 and 8 can be seen as being the result of two basic
processes: either a small (but consistent) number of people are undergoing
substantial amounts of conversion, with the others remaining more or less
stable; or fairly large numbers of people are undergoing incremental
changes in opinion.

The latter position is consistent with the aggregation/cultivation type
approaches taken by Zaller (1992) and Iyengar (1991). The former, on the
other hand, would necessitate a reevaluation of the exact nature of media
impacts on viewers, to a position more consistent with Mueller’s idea of
alienation of sub-groups.

A quasi-experiment designed to evaluate which of these two possible
models holds would almost inevitably require a long-term panel study of
several years. Mortality among members of the panel could be reduced by
making ﬁnancial inducements substantial enough to encourage them to
remain in the study. (A relatively low cost way of doing this would be to offer
inducements in the form of savings bonds.)

A ﬁnal area of further research more clearly related to the speciﬁc
ﬁndings of this study is into the nature of the long term relationship
between policy action and public opinion. As pointed out earlier, in the
overall model and one of the sub-analyses the relationship between these

194

two was negative in sign, a ﬁnding which would have been completely
unexpected had it not been for 'II'umbo’s (1995) earlier, similar, ﬁnding.

The genesis of this effect, however, is unknown. What is known is
that the the effect seems to be tied to the two-year cycle of congressional
elections, suggesting that it may be tied to the nature of the debate and
discourse which surrounds the election. In theoretical terms, there are a
number of potential explanations:

* Distrust: As McAneny (1995) has again demonstrated, “political
ﬁgure” is among the least trusted professions in the nation. It is possible
that as campaigning politicians discuss their accomplishments, their
listeners assume that those accomplishments must somehow, 3 mind, be
wrong.

* Dissonance: Festinger (1957) has pointed out the possibility of
attitude change as a result of decision making. Voting, of course, is a
decision making process; having made the decision in favor of one
candidate (and his or her positions) in one election, in the next the voter’ s
sense of dissonance may be reinforced by attacks on the actions of the
elected ofﬁcial by the opponent.

* Reactance: Brehm has pointed out that, under certain
circumstances, people reject things which they would otherwise desire if
the things are presented unexpectedly or in an unexpected manner. It
could be that many voters ideologically desire certain things, but resent
them when presented with them in the form of legislation. (This would be
symptomatic of a deep-seated, underlying anti-Federalistic value in US
citizens.)

A reactance-like position is viable when one considers the nature of

political debate in the US, at least as characterized by an issue network (or

195

similar) conceptualization: as an issue arises, issue networks develop, each
advocating different solution. These issue networks may be equally
balanced on either side of the issue, but when policy-makers choose one of
the alternative solutions proposed and legislate it into action, issue
networks advocating other solutions from both sides of the issue are
alienated.

Empirically exploring whether one or more of these or other
explanations hold depends in part in the nature of the theoretical position
being tested. However, it is clear that opinion polling is generally far too
superﬁcial in its approach to determining how the American public feels
about and reacts to it political representatives and their actions. The
question far too infrequently asked in opinion polls is “Why?”

The nature of an exploratory study is that it raises questions, and
again this study is no exception. The issue network approach was shown to
have some organizing utility, albeit not necessarily validity as a theoretical
position: it remains to be formally tested. As pointed out above, negative
relations between the various agendas and public opinion, which were
unexpected, might be the result of any of a variety of processes. While
overall effect sizes were not calculated, it is clear that much of the variation
in public opinion remains unaccounted for. The border between the the
policy agenda and the media agenda needs to be explored more thoroughly,
both theoretically and empirically. In short...in very short...there is a great
deal yet to be done. More research is needed in this area.

APPENDICES

APPENDDC A

1%

Appendix A

E-mail message from Libertarian candidate Harry Browne

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>>> To Libertarians Everywhere

>>> By Harry Browne

I want to express my deep gratitude to Libertarians all over America
* For your hard work and dedication in taking our message as far and

wide as possible.

* For the many kindnesses you have shown Pamela and me over the past two
years.

* For the confidence you placed in me to carry the Libertarian message
to the public.

As I write this, we don't have final vote totals. But, even so, there's
no question we have a great deal to be pleased about.

Our total vote will far surpass the 1992 total -- close to doubling it.
Based on the media coverage received, we far outpaced the other

candidates. We apparently received about 1/18 of Ross Perot's vote
total, while getting less than 1/100 of his media coverage. We got

197

roughly the same vote as Ralph Nader, while receiving less than a fifth
of his media attention. Evaluating our performance this way, it was even
better when measured against the coverage given Clinton and Dole. And we
far outpolled all the other small parties.

For a $3 million campaign and a party with 20,000 members, we achieved a
great deal.

But it's obvious that we will never break into the big leagues with a $3
million campaign.

The task ahead of us is clear: we have to create a party so big, so
strong, so well-financed that in the year 2000 no one can ignore us. We
have to make an enormous splash before and throughout the next election
year, so that the media will have to give us the same attention and
respect they give to the two old parties. We have to be so well known to
the public that the Republicans and Democrats can't hold a debate
without us. And if they decide not to hold the debates at all, then we
must have an army of people so large that we can carry our message door-
to-door to every voter, and we must have the money to tell our story
through advertising.

Is this a realistic goal? Yes. It is a formidable goal, but far from
impossible. We are already well along the road to that goal . . .

* We have doubled the party's membership in just the past two years. And
our new compatriots aren't going to go away.

* We have already made inroads, small but significant, into the business
and investment community -- to where the money is.

* The Internet has become our bailiwick. And it will be more and more
influential in politics in the coming years. Libertarians know how to
use it, and we'll always be in a position to make the most of any new
technology that develops.

* We have established wonderful relationships in talk radio. Over 300
radio and TV talk-show hosts endorsed the idea of my being in the
Presidential debates; 69 of them endorsed me for President. We have
established excellent relationships with popular talk-show hosts such as
Michael Reagan, Art Bell, Mary Matalin, Oliver North, Blanquita Cullum,
Barry Farber, Randy Jackson, Alan Combes, and dozens of other syndicated
and big-city personalities who are now glad to hear from us whenever we
have something we want to say.

* We have developed good relationships with many people in the print
media -- editors at political magazines, columnists, and local daily
newspaper editors. Over 75 publications or columnists endorsed my being
in the debates, of which 21 endorsed me for President. We will continue
cultivating these relationships.

Thanks to this campaign, everyone in politics and the media knows who we
are and what we stand for.

198

These may seem like small satisfactions. But, in fact, they are an
important foundation for the work ahead. We need to stay in the public
eye by continuing to have Libertarians on talk radio and television as
often as possible. We need to continue churning out press releases --
showing the Libertarian alternatives to the self-evidently meaningless
proposals of the Republicans and Democrats.

And, more than anything else, we have to build the party membership --
starting right now.

With the numbers of members will come the money.
With the money will come the media attention.

With the media attention will come the public awareness of what we
offer.

Three quarters of the American people think government is way too large.
We are the only party offering those people what they want --
significantly smaller government. There is nothing wrong with our
message or the way we're presenting it. We simply need to have it heard
by more people more often between now and the next election.

We are the only party offering proposals that will make a substantial
difference in the average person's life. We're going to repeal the
income tax so that every dollar you make is yours -- to spend, to save,
to give away as you see fit, not as the politicians think best. We're
going to get Social Security out of the clutches of the politicians so
that your parents and grandparents know their retirement is safe and the
rest of us are free forever from the 15% Social Security tax. We're
going to make the cities safe by implementing the only proposal that
would dramatically reduce crime -— end the insane War on Drugs before it
destroys America. And we're going to restore harmony among all the
ethnic, social, lifestyle, and generational groups in America by taking
away from the politicians the power to inflict one group's values upon
another.

This is what Americans want. This is what we offer. And we are the only
ones offering anything of the kind.

What is missing is the ability to let all Americans know what we offer.
Although we can experiment with short-cuts, the only sure way to acquire
that ability is through the steady building of party membership, which
will lead to the money necessary to attract attention, which will lead
to the media coverage that will make us part of the national discussion.

So let's get started now building the party to the magnitude necessary
for every American to know what we can give them. Let's begin no --
while the others relax and take a year or two off.

I intend to speak out for the party wherever possible -- appearing on
talk radio, television, public forums, and in print -- letting people

199

know there is hope for America. I will counsel Americans not to despair
-- not to feel they're alone in their wishes for a government a fraction
of today's size. I will invite them to join us in this great movement to
make America a free country again.

Again, I want to thank you for the honor you have given me -~ allowing

me to be your candidate. And for all the help and encouragement you have
provided. It has been a wonderful two years.

But we're just beginning

APPENDIX B

200

Project Coding Form

 

 

 

Key Code: Coding Date:
On Domestic Issues
Reformist Reformist
Opts for change and opposes gums quo Prefers not to change; if desires change, prefers reversions to a previously
held posrtron
Democratic Democratic

Favors full extension of electoral rights to all persons

Libertarian
Supports civil liberties such as free speech and the right to protest

Regulatory and Interventionist

Backsthemanagementofbusinessandtheecamybythe
government

Centralist

Using the Federal government to set and enforce national standards and
regulate state and local goverranents

Humanitarian
Favoring a social welfare system for the care and protection of society
in general and thelowerclassinpartiailar

Egalitarian
Advocating equal treatment for all and perhaps equal conditions for all

Permissive
Tolerating and often approving of non-traditional lifestyles and practices

Internationalist
Supporting US. involvement in the world

Multinational
Backing the United Nations and other international efforts

Non-Militarist
Preferring non-military solutions to international disputes
Pro-détente

AdvocatinggoodrelationswithCommunistnatiarsandnotanphasizing
anti-communismasacomerstoneof foreign policy

 

Favors occasional restriction d electoral rights based on psychological,
social, or economic grounds

Libertarian

Favorsrestrictiondcivil rightsin someindividualcasesinfavorofthe
protection of society as a whole

Regulatory and Interventionist

Opposes intervention of government in bu-ess affairs

Centralist
Prefers minimizing power of federal government and leaving the establish-

ment of standards to states and municipalities

Humanitarian

Favors protection of society by means of employment, and by private and
secular institutions

Egalitarian

Prefers a meritocracy where positions and conditions are earned rather than
set by Federal legislation

Permissive

Approving of traditional lifestyles and practices over nan-traditional ones

On International/Foreign Policy Issues

Internationalist
Prefers US. to address domestic concerns; i.e. ”America first"

Multinational
Backs US. and allied opinions against world opinion

Non-Militarist
Rdusestomleoutmilitaryactimasapolicytool

Pro-detente

Calls for suspicion dcomrnmist motives and prefers action to counter
communist hegemony

 

Check LIBERAL points here

 

 

Check CONSERVATIVE points here

 

 

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