Gender-responsive HIV prevention and care research with transgender communities: lessons learned from Peru
Bibliographic record
Abstract
Globally, transgender, nonbinary, and gender diverse (trans) people experience HIV inequities. Calls have been made to engage trans communities in HIV research. Yet few resources exist on how to not only engage with, but center trans communities. We describe our 15+ years of collective experiences partnering on HIV research with trans communities in Peru. Lessons learned include considering context, aspiring for equitable partnerships, continually acknowledging power dynamics, learning from community strengths, practicing reflexivity, building trusting relationships, using a trauma-informed lens, prioritizing knowledge-action, recognizing complex community dynamics, and iteratively implementing gender-responsive praxis. We discuss the need for gender-transformative approaches in HIV epidemiological and interventional research that disrupt existing ideologies and systemic power structures that privilege cisheteropatriarchy (cisgender as the norm) and essentialist understandings of gender (male-female gender binary). The science of community engagement requires more attention in HIV prevention and care research that centers global trans communities' expertise and needs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".