The TRANScending Love Arts-Based Workshop to Address Self-Acceptance and Intersectional Stigma Among Transgender Women of Color in Toronto, Canada: Findings from a Qualitative Implementation Science Study
Bibliographic record
Abstract
Abstract Purpose: Transgender (trans) women of color's HIV vulnerabilities are shaped by social exclusion and intersectional stigma. There is a dearth of tailored HIV prevention interventions with trans women of color in Canada. The objective of the study was to explore trans women of color's HIV prevention priorities and to pilot test an intervention developed from these priorities. Methods: We conducted a qualitative implementation science study to develop HIV intervention strategies with trans women of color in Toronto, Canada. First, we conducted a focus group with trans women of color ( n =8) to explore HIV prevention priorities. Second, we held a consultation with trans women of color community leaders ( n =2). Findings informed the development of the TRANScending Love (T-Love) arts-based workshop that we pilot tested with three groups of trans women of color ( n =18). Workshops were directly followed by focus groups to examine T-Love products and processes. Results: Focus group participants called for researchers to shift the focus away from trans women's bodies and HIV risks to address low self-acceptance produced by intersecting forms of stigma. The community leader consultation articulated the potential for strengths-focused arts-based approaches to address self-worth. T-Love participants described how workshops fostered self-acceptance and built connections between trans women of color. Conclusions: Findings demonstrate the feasibility and acceptability of an arts-based strategy with trans women of color to elicit group-based sharing of journeys to self-acceptance, fostering feelings of solidarity and connection. Providing opportunities for dialogue and reflection about individual and collective strengths may reduce internalized stigma among trans women of color.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".