Open Conference Systems, ITACOSM 2019 - Survey and Data Science

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Estimating anti-immigrant sentiment by item count technique
Beatriz Cobo, María del Mar Rueda, Sara Pasadas, Sebastian Rinken

Building: Learning Center Morgagni
Room: Aula 210
Date: 2019-06-07 09:00 AM – 10:30 AM
Last modified: 2019-05-06

Abstract


The measurement of attitudes toward immigration and immigrants (ATII) is potentially subject to distortions. Known technically as social desirability bias (SDB), the divergence of stated from true scores affects any survey on behaviors or attitudes that some interviewees are unwilling to disclose. Thus, when unfavorable ATII are perceived to carry ethnic or racial overtones, survey respondents with hostile views may choose evasive or dishonest answers. This possibility is especially evident regarding the affective core of prejudice: anti-immigrant sentiment (AIS). And even regardless of such connotations, survey respondents might silence their misgivings to project an image of hospitality. Hence, unless specific techniques are employed to elude SDB, surveys are likely to underestimate unfavorable ATII by an unknown margin. In our study, we will discuss the use of indirect questioning techniques, specifically item count technique, will show more valid and reliable estimates than the direct technique.


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