“Look Me in the Eye”: Empathy and the Transmission of Trauma in the Refugee Determination Process
Bibliographic record
Abstract
Debates between refugee advocates, institutional actors and the wider public regarding refugee claimants often evoke anger, fear and sadness, as well as more positive emotions such as compassion, suggesting a complex societal emotional response toward refugee stories. This article analyses the emotional interactions surrounding refugee determination hearings, as reflected in the discourse of administrative judges and refugees. Our results show that the concepts of empathy and compassion are often used by judges to confirm the benevolent image that the administrative tribunal wants to project as a representative body of the host country. However, the very unequal power relations of the hearing setting structure the transmission of the refugee stories in a way that often prevents an emotional encounter between decision makers and refugees. Beyond the specific context of the refugee determination process, these results illustrate how prevalent psychological models of empathy and the transmission of trauma implicitly reveal a political dimension that validates representations of the helpless but potentially dangerous Other, representations that often underlie broader north-south power relations.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.031 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| 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".