Greentree White Paper: Sexual Violence, Genitoanal Injury, and HIV: Priorities for Research, Policy, and Practice
Bibliographic record
Abstract
The links between sexual violence, genitoanal injury, and HIV are understudied but potentially significant for understanding the epidemic's disproportionate impacts on young women and girls, particularly in sub-Saharan Africa, other hyperendemic areas, and conflict-affected regions. A Scientific Research Planning Meeting was convened by the Social Science Research Council at the Greentree Foundation in New York, March 19-20, 2012, bringing together an interdisciplinary group of researchers, clinicians, and policy makers to identify knowledge needs and gaps in three key areas: (1) the role of genitoanal injury on HIV transmission, acquisition, and pathogenesis; (2) the influence of sex and age-related anatomic characteristics on HIV transmission, acquisition, and pathogenesis; and (3) the role of heterosexual anal intercourse in HIV transmission. This article reflects the consensus that emerged from the Greentree Meeting regarding priority scientific research questions in these three areas, associated data collection and measurement challenges and opportunities, and implications for policy and practice.
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 | 0.024 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.025 | 0.016 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".