Perspectives on the implementation of peer navigation with street-connected youth for HIV care
Bibliographic record
Abstract
Peer work is becoming a more common asset to multidisciplinary healthcare teams working with marginalized populations. The Peer Navigator Project is an implementation science study that sought to adapt and scale up peer navigation in HIV care for street-connected youth. This paper presents a qualitative thematic analysis of interview data to understand the complexities and nuances of peer navigation, including the experiences of a Peer Navigator working with street-connected youth in London, Canada. Through the analysis 5 themes were developed: 1) Expansiveness of the Peer Navigator role, 2) Social locations in peer work, 3) Differentiating peer work, 4) Boundaries, and 5) Care for peer workers. Recommendations for organizations seeking to implement peer work include: 1) Opportunities to prevent workplace stress and burnout, 2) Differentiating and valuing peer work, and 3) Promoting health and wellbeing. Despite the inherent challenges of the role, the value to clients and peers cannot be understated.
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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 | 0.009 | 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 | 0.015 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".