Borders of belonging: challenges in access to anti-oppressive mental health care for Indigenous Latinx gender-fluid border-youth
Bibliographic record
Abstract
Many voices have called for decolonizing psychology as a profession and underscored the necessity of building and utilizing a counseling framework that rejects the rigidity of the gender binary and is mindful of the intersectional positionality that implicates subjectivities in complex vectors of oppression, invisibility, and marginalization. But how does one integrate and apply these complex constructs in a culturally relevant clinical practice? The gap between theory and practice appears to have widened, by both action and omission. Moreover, a myriad of clients run the risk of becoming re-oppressed by hegemonic practices in mental health services in Canada. Gender-fluid youth without immigration status who speak languages other than English are either pathologized or rendered invisible by academic discourses and clinical training practices in university settings. Using a critical approach to personality psychology and drawing upon extensive field research, this work discusses the challenges faced by Indigenous Latinx border-youth in accessing anti-oppressive mental health services in Toronto, Canada. The study conducted between 2010 and 2016, in which six Indigenous Latinx gender-fluid youth were interviewed, employed a qualitative narrative inquiry methodology and used a narrative story map tool to analyze data. Grounded in these research findings, this article highlights the necessity of implementing a culturally relevant and social justice–based training model for mental health care providers. Such training must include an ongoing critical examination of the socio-political underpinnings that ground clinical psychology’s epistemology, rather than adapting hegemonic therapeutic models and practices to a “population at risk.”
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".