Self‐protection and growth as the motivational force behind majority group members' cultural adaptation and discrimination: A parallel mediation model via intergroup contact and threat
Bibliographic record
Abstract
What motivates majority group members to adapt to or reject cultural diversity? Considering the relevance of personal values on our attitudes and behaviours, we inspected how self-protection and growth predict levels of discriminatory behavioural and cultural adaptation intentions towards migrants via intergroup contact and perceived intergroup threats, simultaneously (i.e., parallel mediation). Specifically, positive contact between groups is known for reducing prejudice through diminishing perceived intergroup threats. Yet current research emphasises the role of individual differences in this interplay while proposing a parallel relationship between perceived intergroup threats and contact. Also by inspecting cultural adaptation and discriminatory behavioural intentions, the present study examined more proximal indicators of real-world intergroup behaviours than explored in past research. Using data from 304 US Americans, structural equation modelling indicated a good fit for a parallel mediation model with growth relating positively to cultural adaptation intentions and negatively to discriminatory behavioural intentions through being positively associated with intergroup contact and negatively with perceived intergroup threats, simultaneously. The reverse was found for self-protection. These findings stress that personal values constitute a relevant individual difference in the contact/threats-outcome relationship, providing a motivational explanation for majority group members' experience of cultural diversity in their own country.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".