The Intersectional Integration: Examining The Integration Experiences Of Middle Eastern LGBTQ+ Refugees In Canada and Service Providers Response
Bibliographic record
Abstract
The intersectional identities of Middle Eastern LGBTQ+ (ME-LGBTQ+) refugees expose them to different forms of discrimination and persecution throughout the asylum experience, whether in their home countries, proxy countries or even in Canada, which results in increased difficulties and challenges in integration. By interviewing six ME-LGBTQ+ refugees and conducting a content analysis on 27 websites of refugee-serving organizations, this study explores how the intersectional identities of ME-LGBTQ+ refugees have shaped their integration, and examines the role of the services providers in response to their intersectional integration. The findings revealed that ME-LGBTQ+ refugees suffered intersectional forms of discrimination at the intersection of nationality with gender and sexuality, which resulted on aggravated mental stresses, in addition to gaps in access to services which ME-LGBTQ+ refugees mitigated through their personal solidarity networks. The content analysis revealed gaps in mental health service provision and representation of LGBTQ+ refugees coupled with a complex and overlapping structure of services that hindered the ability of ME-LGBTQ+ refugees to leverage these services. Recommendations include allocating more efforts to understanding the intersectional backgrounds of ME-LGBTQ+ refugees, providing tailored orientation and guidance services in their native language and creating LGBTQ+ friendly housing communities and safe spaces that would allow ME-LGBTQ+ refugees to socialize, express their identities and feel safe, and, therefore, facilitating their successful integration in Canada. Keywords LGBTQ+, Refugees, Immigrants, Canada, Toronto, Middle Eastern, Service providers, Resettlement organizations, Refugee organizations, intersectionality.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.001 | 0.003 |
| 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".