Victim and Perpetrator Groups' Responses to the <scp>C</scp>anadian Government's Apology for the Head Tax on <scp>C</scp>hinese Immigrants and the Moderating Influence of Collective Guilt
Bibliographic record
Abstract
E uropean and C hinese C anadians' perceptions and expectations of the C anadian government's apology for the head tax placed on C hinese immigrants during the early twentieth century were examined, along with C hinese C anadians' willingness to forgive the transgression. Among both E uropean and C hinese C anadians, beliefs about the importance attributed to the event and perception of the apology as deserved and sincere heightened expectations of improved intergroup relations. Collective guilt acceptance among E uropean C anadians heightened the relation between perceived sincerity and positive expectations, whereas collective guilt assignment by C hinese C anadians heightened the relation between sincerity and forgiveness. A one‐year follow‐up of whether C hinese C anadians were equally satisfied with the apology indicated that their willingness to grant forgiveness had waned, and although on the whole expectations of improved relations were met, those who assigned more collective guilt were less convinced. Intergroup apologies and their effectiveness at facilitating intergroup relations are discussed.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".