Sri Lankan Tamil Diaspora: Contextualizing Pre-migration and Post- migration Traumatic Events and Psychological Distress
Bibliographic record
Abstract
The objective of this study was to generate a deeper understanding of the influence of pre- and post-migration traumatic experiences on refugees’ psychological distress, including historical, political and social factors. This dissertation used a multi-method design to examine the impact of trauma on the psychological well-being of refugees. Further, the design included a qualitative component to provide a contextual framework for understanding refugee psychological distress that is not limited to an analysis of a disease model alone but by also making connections to important historical, social and political events. Post-Colonial, Refugee, Trauma and Feminist theories are used as analytic lenses to explain the social structures and events contributing to refugees’ pre- and post-migration traumatic events, and psychological distress. This was an international study that spanned two continents. Sampling included 50 Sri Lankan Tamil refugee participants who lived in Chennai, India and 50 Sri Lankan refugees in Toronto, Canada. Inclusion criteria included a residency period of the last 12 months in either of the sampling sites, and participants 18 years of age or older. Participants from Toronto were recruited through social service agencies and associations, and participants from Chennai were recruited from refugee camps, and the Organization for Elam Refugee Rehabilitation. Tamil versions of the Harvard Trauma Questionnaire, the Post-Migration Living Difficulties Questionnaire, and the Symptoms Check List – 90R were utilized to measure participants’ pre- and post-migration traumatic events and psychological distress. The Harvard Trauma Questionnaire contained qualitative open-ended questions to triangulate the quantitative data in identifying and exploring the impact of contextual influences. Results showed that post-migration traumatic event scores positively predicted psychological distress, and refugee claimants living in Canada had the highest scores on pre-migration and post-migration scores. The qualitative analysis revealed themes related to civil war and resettlement as significant issues. Implications of these findings support the development of a multi-level approach within social work practice which emphasizes contextual issues, focuses on individuals, and promotes social advocacy. Recommendations for future research point to conducting longitudinal studies to assess the cumulative effects of historical, social and political factors on refugees and identify resiliencies that mobilize their capacity to survive.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| 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".