An Exploration of Factors Related to Suicidality and Trauma in LGBTQ Refugees and Asylees
Bibliographic record
Abstract
In a global context where attitudes towards refugees and asylum seekers as well as LGBTQ human rights are becoming increasingly virulent, LGBTQ refugees and asylum seekers are at an increased risk for a number of mental health problems, including suicidal ideation and attempts. While evidence has shown high prevalence of suicidality among refugees and LGBTQ people separately, no studies have specifically examined this phenomenon among those who are members of both groups – that is, LGBTQ refugees and asylum seekers. Thus, the purpose of this dissertation is to explore factors related to the experiences distress, trauma, and suicidality among LGBTQ refugees and asylum seekers. Utilizing a theoretical framework combining cumulative disadvantage theory, the minority stress model, and queer migration theory, a secondary qualitative analysis was conducted of interviews with 26 LGBTQ refugees and asylum seekers in the U.S. and Canada. Thematic analysis was applied to understand the experiences of trauma, distress, and suicidality among LGBTQ refugees and asylees. The results of this study indicated three themes related trauma, distress, and suicidality: internal and interpersonal supports, secondary exposure to trauma, and retraumatization. The findings are discussed in light of the theoretical framework and the concepts of secondary exposure to trauma and retraumatization. Finally, the study’s limitations as implications for social work and recommendations for future research are presented.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".