In a polarized opinion climate, people may refrain from participating in publicly observable political activities that make them vulnerable to scrutiny and criticism by others who hold opinions that differ from their own. We took a dispositional approach to testing this claim by determining whether people who are relatively more influenced by the climate of opinion when choosing whether or not to voice an opinion, measured with the Willingness to Self-Censor scale [Hayes et al. International Journal of Public Opinion Research 17 (2005) 298], are also relatively less likely to engage in public political activities. In a poll of residents of the United States, we found that even after controlling for interest in politics, political ideology, ideological extremity, political efficacy, attention to political news, dispositional shyness, frequency of political discussion, and demographics, dispositional self-censors reported having engaged in relatively fewer public political activities over the prior 2 years compared to those less willing to censor their own opinion expression. These results are consistent with our interpretation of political participation as a social process that is governed in part by the social psychological implications of participation to the person. At a larger theoretical level, our findings connect the literature on opinion perceptions and opinion expression with research on political participation.
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Willingness to self-censor should not be confused with a related construct, “self-monitoring,” which refers to “self-observation and self-control guided by situational cues to social appropriateness” (Snyder, 1974). Self-monitors may choose self-censorship as a behavioral strategy in some contexts, but self-censors are not necessarily self-monitors, at least as defined by Snyder. Indeed, data collected during the development of the willingness to self-censor scale reveals no linear association between the two (r = 0.02, n = 353 college students). Scores on the willingness to self-censor scale have been correlated (n = 156 college students) with the four subscales of Lennox and Wolfe’s (1984) revised self-monitoring scale, designed to overcome some of the limitations of Snyder’s conceptualization and measurement of self-monitoring. Respondents high on the willingness to self-censor scale also tend to score relatively high on the “attention to social comparison information” (Hayes et al., 2003) and “cross-situational variability in behavior” dimensions, but there was no systematic relationship between willingness to self-censor and “acting ability” and “ability to modify self-presentation.”
The questions described in this paper are only a small subset of the questions asked to each participant during the telephone interview. There were several investigators competing for interviewer time, and both time and financial constraints limited the number of questions we could include for the purpose of this study. We did conduct an analysis described by Kline (1998, pp. 264–266) similar to the one described in the Results section in which we accounted for the lower reliability in measurement produced as a result of using only a single indicator of shyness. In this procedure we estimated reliability of a latent shyness variable operationalized with our single indicator to be 0.90 using data from the college student sample and treated the other variables as manifest in a linear structural equation model estimating political participation. Even after accounting for increased measurement error, the substantive results were the same.
Income is frequently controlled for in studies of political participation but we did not include it in our analyses because of the large number of respondents (n = 120) who chose not to provide their income during the interview. In one analysis not reported here we did include income as a predictor variable. Controlling for income did not substantively change the results.
When “don’t know” options were provided, these were treated as refusals and coded as missing.
Negative binomial regression is very similar to Poisson regression, except that negative binomial regression includes a dispersion parameter that allows the conditional variance to differ from the conditional mean. Poisson regression is a special case of negative binomial regression in which the dispersion parameter is zero. In our model, the dispersion parameter (using the mean dispersion model) was statistically different from zero, indicating negative binomial regression was more appropriate than Poisson regression. For details on the differences between Poisson and negative binomial regression, see Gardner, Mulvey and Shaw (1995) or Long (1997). We did also estimate the model using Poisson regression and the substantive results were the same.
We did conduct a corresponding OLS regression. As would be expected, the OLS estimation errors were heteroscedastic using the Breusch–Pagan test, χ2 (1) = 64.46, p < .0001. Nevertheless, the substantive results were the same as produced by negative binomial regression.
Although M-plus has implemented FIML for linear models, it has not for negative binomial regression or Poisson regression. The comparisons we make here are between the coefficients for a linear regression using maximum likelihood estimation and the negative binomial regression reported in Table 2 based on listwise deletion, as well as between an OLS regression using listwise deletion and one using FIML. As noted in footnote 6, OLS regression and negative binomial regression produced substantively identical results, so this comparison seems relevant. Unfortunately, we have no clear and sensible model for nonignorable missingness, and there are few statistical algorithms implemented in software to handle the nonignorable case.
If this explanation is correct, then there should be no relationship between willingness to self-censor and engaging in private political activity, such as voting. We did include a question in the survey asking respondents whether they voted for an elected official in the last 2 years. Consistent with our argument, in a multiple logistic regression there was no statistically significant relationship between willingness to self-censor and voting (partialling out the same covariates). This is the only question about political activity we asked that could be unequivocally construed as private.
The participation questions on the survey were designed by a different investigator with a different purpose and aren’t precisely worded enough for us to examine this question empirically in these data.
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Items on the willingness to self-censor scale (Hayes et al., 2005a). Responses are made on a 1 (strongly disagree) to 5 (strongly agree) scale, anchored in the middle by “neither agree nor disagree”.
It is difficult for me to express my opinion if I think others won’t agree with what I say.
There have been many times when I have thought others around me were wrong but I didn’t let them know.
When I disagree with others, I’d rather go along with them than argue about it.
It is easy for me to express my opinion around others who I think will disagree with me. (R)
I’d feel uncomfortable if someone asked my opinion and I knew he or she wouldn’t agree with me.
I tend to speak my opinion only around friends or other people I trust.
It is safer to keep quiet than publicly speak an opinion that you know most others don’t share.
If I disagree with others, I have no problem letting them know it (R)
R = reverse scored
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Hayes, A.F., Scheufele, D.A. & Huge, M.E. Nonparticipation as Self-Censorship: Publicly Observable Political Activity in a Polarized Opinion Climate. Polit Behav 28, 259–283 (2006). https://doi.org/10.1007/s11109-006-9008-3
- Political participation
- Public opinion
- Opinion expression