Efficacy of Supports Available to Marginalised Sexual Minority Youth Through an Attachment Theoretical Lens
Bibliographic record
Abstract
The prevalence of homeless youth in Canada has been increasing with over 30,000 youth homeless, and Indigenous and sexual- and gender-minority youth being overrepresented. A disparity exists amongst marginalised sexual-minority youth (MSMY) who experience bullying, victimisation, mental health challenges, and homelessness disproportionately to their cis gendered peers. The author drew on existing literature to examine the unique needs of MSMY who are street involved, homeless, and/or transient and the efficacy of available community supports through an attachment theoretical lens. Common themes that the author synthesised from the literature are levels of victimisation, prevalence of relational and social trauma, cultural needs, and protective factors of sexual-minority youth (SMY). The findings suggest that systemic discrimination (i.e., sexism, racism), organisational systems (i.e., school systems, governments), adverse childhood experiences (ACEs) and relational trauma, and the lack of natural supports are associated with poor outcomes for MSMY. However, accessibility to resources, communities’ acceptance, collaboration amongst professionals, and therapeutic tools such as affirmative cognitive behavioural therapy (CBT) and mindfulness interventions are associated with positive health outcomes. The literature review reveals a gap in research on MSMY in Canada, and further research in this area is warranted. Lastly, the author makes recommendations based on empirical findings and suggestions for future research.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".