“We don’t talk about Trauma”: El Salvadorians and Community Trauma
Bibliographic record
Abstract
This article draws upon data from a Canadian study funded by the Social Sciences and Humanities Research Council. The focus was on how trauma has been experienced by three communities who have been historically marginalized: The El Salvadorian community, Indigenous peoples and those identifying as 2STLGBQIA+. The focus of this article is on the Salvadorian diaspora in Canada, which has the shared experience of historical colonial trauma; on-going coloniality leading to civil war; and poverty, leading to forcible displacement. The latter resulted in re-negotiating their lives in the diaspora and transnationally in El Salvador. As with Indigenous and 2STLGBQIA+ communities, Salvadorians in Canada share experiences of multiple oppressions and marginalization based, in part, on perceptions of belonging and worth, rooted in racism. Exploring notions of community development as it exists in diaspora communities must include a history of war, resettlement and marginalization that contribute to trauma at the community level.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".