Temporal Causal Links Between Outgroup Attitudes and Social Categorization: The Case of Hong Kong 1997 Transition
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Bibliographic record
Abstract
Social identity theories have posited that people's social categorization renders ingroup favoritism and outgroup discrimination. However, studies conducted during political transitions (South Africa's democratic election and East-West German unification) have revealed mixed directions of the causal links between social categorization and intergroup attitudes. To further address this issue, we conducted two longitudinal studies during the handover of Hong Kong in 1997. Study 1 revealed mixed temporal causal links between Hong Kong participants' social categorization and their attitudes toward Chinese Mainlanders across four waves. In Study 2, we conducted a summer camp in which Hong Kong participants came into contact with new immigrants from Mainland China. In this condition, Hong Kong participants' prior attitudes toward Mainlanders predicted their subsequent social categorization. These findings were interpreted in terms of intergroup relations during political transitions.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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