Hijab and enclothed cognition: The effect of hijab on interpersonal attitudes in a homogenous Muslim-majority context
Why this work is in the frame
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Bibliographic record
Abstract
Stereotyping and discrimination against hijab-wearing women have been studied extensively in many Western countries, which are home to Muslim diasporas. However, there is a paucity of research on Muslim-majority countries. The purpose of this study is to address this gap and explore interpersonal attitudes toward both hijab-wearing and non-hijab-wearing women, in Pakistan, a Muslim Majority country. In this paper, we used the presence or absence of hijab as the independent variable, and measured competence and warmth using items from the Stereotype Content Model (SCM), as well as social and task attraction using items from the Interpersonal Attraction Scale (IAS) as dependent variables. Study 1 included 352 undergraduate students, while Study 2 involved 151 human resource professionals. The findings from both studies were consistent in suggesting that participants had a higher attribution of competence, warmth, and social and task attraction toward the hijab-wearing women compared to the non-hijab-wearing women. Conversely, participants in the non-hijab condition attributed lower levels of warmth, competence, and social and task attraction. We interpret these findings such that in a homogeneous society, individuals who strongly identify with and internalize Muslim culture, and exhibit a preference for their own cultural and religious values (cultural endogamy), attribute higher levels of competence, warmth, social attraction, and task attraction to the protagonist who wears hijab. This research has implications for employment opportunities and attitudes toward women in the workplace in Muslim-majority countries, both for hijabis (women who wear a headscarf) and non-hijabis (women who do not wear hijab).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it