Beyond buzzwords: toward a community-based model of the integration of HIV treatment and prevention
Bibliographic record
Abstract
Propelled by increased global access to Highly Active Anti-Retroviral Therapies, the integration of HIV treatment and prevention has emerged as an important organizing concept of pandemic response. Despite its potential significance for community-based AIDS organizations (CBAOs) little research on integration has been done from a community-based perspective. This paper responds to that gap in the literature. With a view to moving what can be an abstract concept to the level of concrete practice, we offer a community-based model of the integration of HIV treatment and prevention. The model is based on research conducted in 2006-2007 with front-line staff from CBAOs across Canada carried out in partnership with the Canadian AIDS Treatment Information Exchange. The model is grounded in three central dimensions of a community-based perspective on integration deriving from our research: the phenomenological primacy of front-line service work, a comprehensive notion of treatment and prevention, and the importance of social context. The model is intended as a conceptual resource that can assist CBAOs in formulating practical responses to new demands for integrated service provision.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".