Feeling is NOT Mutual: Political Discussion, Science, and Environmental Attitudes by Party Affiliation

ABSTRACT

In this paper, we extend the work that has been done examining the influence of interpersonal communication on people’s trust in scientists and environmentalists and whether these levels of trust are associated with support for specific science and environmental policies. Previous work has shown that discussions with others can influence perceptions of important issues such as attitudes about climate change. Our study extends this line of inquiry by showing that the relationship between political discussion and evaluations of actors in society is moderated by party identification. We also find that evaluations of scientists and environmentalists is associated with support for science and environmental policies. Moreover, we assess whether these associations vary over time. In the end, our findings provide further evidence that interpersonal communication can influence important science and environmentally related outcomes. Moreover, it shows that these relationships could change over the course of time.

KEYWORDS:

• Interpersonal communication
• vaccines
• environment
• dynamic process

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Although these items were measured for more years than what is included in this paper, we could only include years where all three of our key variables (i.e., discussion, evaluations of environmentalists, and support for government spending on the environment) were included together in the data set. All three items first appeared in the data set in 1990. 1998 was excluded because the evaluation of environmentalists item was not included on the survey that year. 2002 was the final year all three of these items appeared on the survey together.

2 For the cumulative data file, the ANES has recoded the high number to 97. In essence, the scale technically ranges from 0 to 100. However, 98, 99, and 100 are coded as 97 because of the way they have coded missing data.

3 In addition to the analyses presented in this paper, we also ran a set of analyses that added news use as an additional control variable. The argument for including news use would be that our measure of political discussion is simply picking up on the correlation between news and our outcomes. In other words, our findings could be spurious because we have not accounted for news use. Therefore, we re-ran all of our analyses and included news use in the model as an additional control variable. Overall, the results largely remained the same in terms of statistical significance after accounting for people’s level of news use.

4 We also calculated the total indirect correlation for the vaccine perceptions. The total correlation is not significant and is essentially the same as the direct correlation (B = 0.012, SE = 0.014, p > 0.05).

5 We also calculated the total indirect correlation for vaccine school policy. The total correlation is not significant and is essentially the same as the direct correlation (B = 0.019, SE = 0.013, p > 0.05).

6 We report the beta and standard errors when including evaluations of scientists in the model. However, there were no differences in the beta or standard error when removing evaluations of scientists from the analysis.

7 Throughout the paper we are reporting the squared semi partial correlations tied to our coefficients. The squared semi partial correlation is an assessment of unique variance explained by that particular variable. We calculated these from regression models run in SPSS not using the process macro.

8 We also examined whether the relationship between discussion and both perceived benefits of vaccines and support for the vaccine policy in schools varied by party identification. Our results did not find that the relationship between discussion and perceived benefits varied by party identification (B = -0.006, SE = 0.006, p > 0.05). However, we did find that the relationship between discussion and support for the school policy did vary by party identification (B = -0.013, SE = 0.006, p < 0.05). When probing the interaction, discussion was related to higher support for the policy among Democrats. There was no relationship among Republicans. We have also included results from a total correlations analysis in online Appendix D. There was one significant total correlation among Democrats for perceived benefits associated with the vaccine. The remaining total correlations were not significant.

9 We also calculated the total indirect correlation for discussion on support for environmental spending through feelings about environmentalists. The total correlation is not significant and is essentially the same as the direct correlation (B = -0.006, SE = .003, p > 0.05).

10 We also examined whether the relationship between discussion and support for environmental spending varied based on party identification. Our results found a statistically significant interaction (B = -0.012, SE = 0.001, p < 0.05). Specifically, discussion was associated with greater support for environmental spending among Democrats and lower support for environmental spending among Republicans. We also calculated the total correlations, which appear in Appendix E. In general, we find the same pattern of results with similar findings.

11 We also calculated the total correlations for these findings, which appear in online Appendix E. We generally find the same pattern of results where the relationships are stronger in the early 1990s compared to the early 20000s.