Eliciting critical hope in community-based HIV research with transgender women in Toronto, Canada: methodological insights
Bibliographic record
Abstract
Critical hope centres optimism and possibilities for change in the midst of struggles for social justice. It was a central tenet of early participatory pedagogy and HIV research. However, critical hope has been overlooked in contemporary HIV research that largely focuses on risk and biomedical interventions in ways that obscure collective agency and community strengths. We conducted a community-based study with transgender (trans) women of colour in Toronto, Canada to adapt an evidence-based HIV prevention intervention. Participants resisted a focus on HIV, instead calling researchers to centre journeys to self-love in contexts of social exclusion. In response, we piloted three arts-based, participatory methods generated with community collaborators: (i) affirmation cards sharing supportive messages with other trans women, (ii) hand-held mirrors for reflecting and sharing messages of self-acceptance and (iii) anatomical heart images to visualize coping strategies. Participants generated solidarity and community through shared stories of self-acceptance within contexts of pain, exclusion and loss. Narratives revealed locating agency and self-acceptance through community connectedness. Critical hope was a by-product of this participatory process, whereby participants shared personal and collective optimism. Participatory and arts-based methods that centre self-acceptance and solidarity can nurture resistance to pathologizing discourses in HIV research. Centring critical hope and participant-generated methodologies is a promising approach to transformative health promotion and intervention research. These methodological insights can be engaged in future participatory work with other marginalized groups facing dominant biomedical risk discourses. Critical hope holds potential as a participatory health promotion strategy for envisioning possibilities for sustainable change.
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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 | 0.051 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".