ESRA 2019 Programme at a Glance
Assessing Implicit Attitudes Using General Population Surveys
|Session Organisers|| Professor Elmar Schlueter (Justus-Liebig-University of Giessen (Germany))
Professor Jochen Mayerl (Technische Universität Kaiserslautern)
|Time||Thursday 18th July, 09:00 - 10:30|
Survey researchers typically assess attitudes, broadly defined here as associations between concepts and evaluations, using self-report measures. For example, respondents might be asked to explicitly self-assess their views or feelings toward different immigrant groups on a response scale from 1 (dislike this group very much) to 7 (like this group very much). Alternative to such a direct measurement approach, respondents’ attitudes might also be assessed indirectly using implicit measures. Here, one line of research originating in psychology uses respondents’ performance (e.g. response latencies or categorization errors) on behavioral tasks designed to infer the construct of interest rather to rely on self-reports. Recent years have witnessed an unprecedented proliferation of methods seeking to assess such implicit attitudes, including but not limited to measurement approaches like the implicit association test (Nosek, 2007) or the affective misattribution procedure (Payne et al., 2005). Relying on relatively small, non-representative samples, such methods are routinely employed in psychological research. However, the feasibility and utility of using implicit measures in large-scale survey research based on representative population samples is less clear. This session invites papers that focus on methodological as well as substantive issues arising from coupling measures of implicit attitudes with large-scale population surveys. Contributions may cover but are not limited to the following research topics:
• Innovative measurement approaches of implicit attitudes
• Effects of survey mode and/or sampling methodology on outcomes
• Applications with a substantial focus (e.g. research on intergroup relations or sensitive topics more generally)
Please send your paper proposals (no more than 500 words in length) to:
Prof. Dr. Elmar Schlüter, firstname.lastname@example.org
Prof. Dr. Jochen Mayerl, email@example.com
Keywords: Implicit Attitude measurement, Population Surveys, Innovations, survey mode, sensitive topics
Success or Failure? Researchers' Implicit Associations with Academic Misconduct and with Questionable Research Practices
Dr David Johann (University of Zurich)
Mr Justus Rathmann (University of Zurich) - Presenting Author
Professor Heiko Rauhut (University of Zurich)
Dr Colin T. Smith (University of Florida)
Research deploying Implicit Associations Tests (IAT) has become increasingly popular in the Social Sciences. This is not surprising as such indirect measures promise to circumvent measurement problems caused by social desirability bias, among other things. However, to date, there has not been an application of IAT in Science Studies, although this subdomain of the Social Sciences deals frequently with norm violations, such as academic misconduct and other questionable research practices, that are highly sensitive and susceptible to biased reporting.
Drawing on a survey among researchers at German universities which includes two Single-Category Implicit Association Tests (SC-IAT) we investigate if researchers link implicit associations with academic misconduct (such as data falsification, data fabrication and plagiarism) and questionable research practices (such as gift authorship and self-plagiarism) to academic success or failure. To be more precise, using the SC-IAT we examine whether researchers rather associate academic and professional success than academic and professional failure with "academic misconduct" or "questionable research practices", respectively. The aim of the study is twofold: (a) We aim to learn more about researchers' propensity to engage in questionable behaviour and (b) we intend to identify factors that are related to academic misconduct and questionable research practices.
Application of the Affective Misattribution Procedure in a Large-Scale Survey to Assess Prejudiced Attitudes
Professor Elmar Schlüter (Justus-Liebig-University of Giessen) - Presenting Author
Professor Jochen Mayerl (Chemnitz University of Technology)
Mr Henrik Andersen (Chemnitz University of Technology)
Conducting surveys to assess prejudiced attitudes are typically faced with the problem of social desirability (SD) bias. For decades, survey researchers have tried to assess the ”true” attitudes underlying explicit survey statements which are potentially consciously biased towards social desirability. Different survey methods like scales intended to measure an individual’s need for social approval or trait desirability as well as experimental approaches including Randomized Response Technique or Item Count Technique were developed and tested in survey research. Further, survey researchers have looked at the response latencies of the explicit statements in surveys to get a deeper understanding of the answering process. So far, however, the problem of SD bias still persists. Another stream of research was established for lab experiments in the field of psychology to assess implicit attitudes, i.e. attitude statements that are not under conscious control of the respondents. Two prominent approaches in this field of research are the Affective Misattribution Procedure (AMP) and the Implicit Association Test.
In our study, we adopt the AMP in a large-scale web survey to assess prejudiced attitudes towards various minority- and outgroups (e.g. women, Muslims, homosexuals, Jews, foreigners, refugees, disabled persons and overweight persons). The AMP presents respondents with a prime stimulus (the actual attitudinal object of interest) followed by an ambiguous ‘target’ item (e.g. a Chinese pictograph or abstract painting) that the respondent is then asked to evaluate. Respondents are expressly instructed to ignore the prime. The AMP works because respondents often cannot disentangle affective responses towards prime and target thereby allowing insight into implicit attitudes.
We compare the findings of the AMP with results of more classic survey approaches, i.e. explicit attitude statements after correction for SD scales, response latency analysis and item count technique.