Cross-Group Relationships and Collective Action: How do International Students Respond to Unequal Tuition Fee Increases?
Bibliographic record
Abstract
Although positive cross-group contact can reduce prejudice, it also can undermine disadvantaged group members’ engagement in collective action (CA). However, some initial research suggests that contact with advantaged group members who are openly supportive of the disadvantaged group may not decrease, and may actually increase disadvantaged group members’ CA. This research used the unequal tuition fee increases at Simon Fraser University (SFU) to investigate international students’ CA intentions. We manipulated the contact partner’s (Canadian student) supportiveness and whether Canadian students directly benefited from the unequal tuition fee increases. The results indicated that when Canadian students were beneficiaries of the inequality, supportiveness from a Canadian student increased international students’ intentions of engaging in organizational disloyalty towards SFU (a form of CA) via increased group-based sadness. However, when Canadian students were bystanders, supportiveness decreased intentions of engaging in organizational disloyalty via reduced group-based sadness and fear.
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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 | 0.001 | 0.006 |
| 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 | 0.002 | 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".