PS 320 7

Attitude Stability and Ambivalence

Requirements of Democratic Citizenship

• Effective representation requires consent of the governed.

• Citizens should hold real attitudes:

  • Real attitudes are informed and stable beliefs rather than superficial or vague opinions.

• Citizens should hold informed attitudes:

  • Attitudes are shaped by knowledge and understanding of political issues.

• Citizens should hold stable attitudes:

  • Stability is essential for accountability and informed decision-making in a democracy.

• Implications of attitudinal instability:

  • Raises questions about the validity of public opinion and its representation in democratic processes.

Stability of Attitudes (1958 – 1960)

• Correlation of Same Attitudes Across Issues:

  • Party identification: 0.73 correlation (85.7% same attitude)

  • School desegregation: 0.43 correlation (57.5% same attitude)

  • Employment discrimination: 0.41 correlation (60.0% same attitude)

  • Guaranteed employment: 0.41 correlation (56.5% same attitude)

  • Isolationism: 0.39 correlation (59.6% same attitude)

  • Federal aid to education: 0.38 correlation (57.2% same attitude)

  • Foreign economic aid: 0.34 correlation (48.0% same attitude)

  • Foreign military aid: 0.32 correlation (57.7% same attitude)

  • Federal housing: 0.29 correlation (40.7% same attitude)

Converse’s Conclusions

• Converse’s analysis highlighted that:

  • Large portions of the electorate do not possess meaningful beliefs, even on key contentious issues.

  • Pervasiveness of response instability can be attributed to:

  • Nonattitudes: Citizens often lack thought on issues, indicating a misunderstanding of questions.

  • Randomness of response: Responses may not reflect genuine beliefs but rather randomness.

  • Impression management: Respondents may shape answers to align with social expectations.

  • Implications for democratic theory:

  • Question the legitimacy of public opinion in democratic processes.

Rescuing Citizen Competence

• Various perspectives attempt to explain away response instability, asserting causes like:

  • Context of the 1950s affecting attitudes.

  • Measurement error impacting survey reliability.

  • Surveys influenced by response set bias.

  • Ambivalence and the belief sampling model influencing responses.

  • Miracle of aggregation suggests that individual errors may not impact collective opinion significantly.

Increased Attitudinal Constraint?

• Investigated by Nie and Andersen (1974), questioning whether the 1950s was a non-ideological period:

  • Studies show overall consistency in attitudes over different periods (1956 to 1972).

• Results show shifts in consistency by issue area:

  • Domestic consistency had varied levels of stability, often affected by context.

Illusory Increases in Attitudinal Constraint

• Comparison of old vs. new wording in attitudes indicates shifts:

  • Welfare issues and black welfare attitudes showed varying correlations before and after wording changes, e.g.:

  • Welfare and black welfare: Old = 0.28, New = 0.43

  • Welfare and integration: Old = 0.11, New = 0.30

  • Further implications on measuring stability in social attitudes are considered.

Achen’s Measurement Error Argument (1975)

• Achen posited that instability could arise from:

  • Lack of importance regarding attitudinal constraint and stability.

  • Genuine attitude change versus response instability driven by measurement error.

• Measurement error can derive from:

  • Variation amongst subjects.

  • Variation based on question phrasing.

• Measurement Error Argument:

  • Ambiguous survey questions could make respondents, regardless of stability, appear inconsistent over time.

Calculating Measurement Error

• The following equations help quantify measurement error:

  • $x = p + e$ (observed opinion at time t)

  • $x<em>2 = p</em>2 + e<em>2 = p</em>1 + u<em>1 + e</em>2$

  • $x<em>3 = p</em>3 + e<em>3 = p</em>1 + u<em>1 + u</em>2 + e_3$

• Ultimately allows for measurement of error in surveys.

Correcting for Measurement Error

• The formula for the true score correlation ($r_{tt}$) is:

  • $r_{tt} = \frac{variance \ of \ true \ scores}{total \ observed \ variance}$

• Corrected correlations ($r_{ss}$) can be determined from observed values.

Observed vs. Corrected Correlations

• Example of various correlations:

  • Aid to Blacks: Observed = 0.51, Corrected = 0.95.

  • School Integration: Observed = 0.45, Corrected = 0.80.

  • Others exhibit similar discrepancies showing the effects of measurement error upon perceptions.

Virtues of the Measurement Error Argument

• Suggests that response instability often stems from the randomness of survey methods instead of citizen shortcomings.

• If true attitudes exist, it satisfies democratic citizenship requirements by indicating informed perspectives.

Context and Response Set Bias

• Response instability can result from:

  • Format, order, and wording of questions.

  • Available response options.

  • Social desirability bias affecting honest answering.

  • Acquiescence bias influencing consensus picking.

• All these factors raise important queries regarding citizen competence.

Response Instability: An Illustration

• Data from June 1980 survey indicates:

  • Positive responses to government service cuts varied but highlighted variability in perspectives.

• Example question posed regarding reduction of government services demonstrates inconsistency in positions held by citizens.

Ambivalence and the “Belief Sampling” Model

• Citizens tend not to have fixed attitudes, instead they possess varied, partially consistent thoughts:

  • When answering questions, respondents sample attitudes influenced by recent events.

  • Opinions are constructed anew at the time of questioning, reflecting only accessible ideas.

  • Decision-making reflects immediate thoughts influenced by prominence given by elite cues.

Axioms of the Belief Sampling Model

• Ambivalence Axiom: Most individuals have opposing thoughts about issues.

• Response Axiom: Survey answers represent an average of salient considerations at the moment.

• Accessibility Axiom: The chance of considering any thought is contingent on recent cognitive focus.

Are People Ambivalent?

• Examined through retrospective and stop-and-think probes regarding issues like jobs and aid to blacks:

  • Data illustrates percentages of conflicting considerations across respondents, indicating high levels of ambivalence.

Response Stability and Conflicting Considerations

• Findings indicate:

  • The more consistent a set of considerations, the higher the stability of response.

• Stability varies significantly with the degree of prior consistency observed among respondents.

Collective Opinion vs. Individual Opinion

• Individual opinions show fluctuation due to random errors.

• Collective opinions exhibit considerable stability over time, attributed to the “miracle of aggregation”:

  • Aggregate assessments yield rational outcomes from disparate, often uninformed individual inputs.

• It raises ethical considerations if inconsistent reality leads to systematic bias rather than random noise.

Stability of Collective vs. Individual Opinion

• Evidence from individual stability across two years:

  • Mixed and conflicting results from specific respondents regarding support for government spending.

  • Grouped data (60% changed opinion) highlights individual variability in collective trends.

The Concept of Ambivalence

• Defined as:

  • Simultaneous endorsement of conflicting beliefs towards a context or object (ex. policy choices or candidate support).

• Challenges fundamental beliefs about how attitudes function in political discourse.

Consequences of Ambivalence

• Noted effects include:

  • Reduction in accessibility, stability, and extremity of political attitudes.

  • Increase in response variability affecting candidate evaluations crucially.

  • Makes political participation lower due to hesitance toward aligning with options.

Sources of Ambivalence

• Influenced by:

  • Individual-level traits (political knowledge, cognitive needs, partisan strength).

  • Social network composition affecting exposure to diverse ideas.

  • Political competition encouraging diverse perspectives.

The Dynamics of Ambivalence

• Questions remain about:

  • Whether ambivalence fluctuates and whether trends are consistent across contexts or campaigns.

  • Factors affecting changes in ambivalence levels for individuals.

An Informational Theory of Ambivalence

• Suggests ambivalence arises from information exposure diversity:

  • When individuals receive conflicting arguments, they may internalize conflict.

  • Heterogeneity in information can foster ambivalence.

Pathways of Influence

• Effortful Processing:

  • Greater consideration and focus on information may enhance exposure to conflicting viewpoints (hypothesis: increases ambivalence).

• Social Network Composition:

  • Diverse political networks expose individuals to varied arguments, heightening ambivalence levels.

• Political Competition:

  • Competing interests create environments that encourage consideration of both sides, thereby promoting ambivalence.

A Motivational Theory of Ambivalence

• Examines motivation behind feelings:

  • Individuals operating under directional vs. accuracy motivations may reevaluate standards.

  • Strong partisanship can lead to biases that minimize ambivalence, contributing to polarization.

The Moderating Role of Partisan Reasoning

• Examines interaction between partisan strength and processing:

  • Strong prior attitudes may result in biased consideration sets.

  • Hypotheses suggest strong partisans’ reasoning affects how ambivalence is moderated during processing efforts:

  • Low knowledge may increase ambivalence.

  • Strong knowledge might polarize attitudes further.

The Data

• Based on data gathered from the ANES Panel, composed of multiple survey waves throughout 2008:

  • Included measures of ambivalence and processing requirements.

Measurement Overview

• Various factors evaluated concerning candidate ambivalence:

  • Effortful processing, political knowledge, social network composition, and political competition considered.

Change in Ambivalence (Jan – Oct, 2008)

• Data showed:

  • 57.1% of respondents saw a decrease in ambivalence.

  • 17.3% reported no change, while 25.7% noted increases in ambivalence.

Figures on Candidate Ambivalence

• Statistical representation of candidate ambivalence showcased over the course of the 2008 campaign:

  • Track progression from January through October with surges reflecting dynamism in voter sentiment.

Changes in Ambivalence Analysis

• Statistically explored variations in ambivalence related to several factors:

  • Effortful processing, working through political knowledge, social influences from diverse networks, shifts in political state resilience, and motivational capabilities.

Magnitude of Intervention Effects

• Charted effects on ambivalence across two campaign phases:

  • Evidenced through distinct psychological motivators and cognitive biases emerging through personal dynamics and social pressures.

What Have We Learned?

• Key findings include:

  • Ambivalence is indeed a dynamic phenomenon influenced by various elements.

  • Declinement of ambivalence is observable over time.

  • Understanding of patterns is not uniform, indicating complexity within individual experiences relative to external political stimuli.