When words become borders: Ingroup favoritism in perceptions and mental representations of Anglo-Canadian and Franco-Canadian faces
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Language is critical to social identity, including nationality. However, some nations encompass multiple languages, raising questions about how their citizens perceive members of their national versus linguistic groups. We explored perceptions of Canadian nationality, which consists of two linguistic groups: Anglo-Canadians and Franco-Canadians. In Study 1, we used reverse correlation methods to visualize how Anglo- and Franco-Canadians mentally represent the faces of linguistic ingroup and outgroup members, and of Canadians in general. Structural similarity analyses and subjective ratings of the resulting images showed that both groups mentally represented Canadians as more similar to their own linguistic ingroup. In Study 2, Anglo-Canadians and Franco-Canadians rated photos of real Anglo- and Franco-Canadian targets. Both samples showed some ingroup favoritism when inferring their traits but only Anglo-Canadians could accurately differentiate group members. Differences between Anglo-Canadians and Franco-Canadians therefore extend beyond language, with linguistic groups impacting impressions before any words are spoken.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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