Moving beyond behaviour: Advancing HIV risk prevention epistemologies and interventions (A report on the state of the literature)
Bibliographic record
Abstract
This paper is based on an extensive literature review of academic, policy and 'grey' literatures on the intersections of culture and the global HIV/AIDS pandemic commissioned by UNESCO. It highlights that the review exposed a dominant conceptual perspective that poorly captures structures of vulnerability, particularly structures that expose entire populations to risk in relatively uniform ways. Stemming from this, the review revealed a series of specific topical areas in need of further research including masculinities, transactional sex, infrastructural deficits in health and education, fragile states and global governance. For each of these topical areas the authors demonstrate the relationship to the conceptual limitation, summarise relevant research in this area, and provide evidence of applicability to public health interventions. In pursuit of more effective interventions, this paper draws attention to some of the conceptual limitations of current approaches to understanding the pandemic, and calls for interventions that move beyond individual behaviours to address structures that shape individual behaviour and make entire populations more vulnerable to HIV.
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 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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".