Review: sexual abstinence only programmes do not affect STIs or HIV risk behaviours in high-income countriesCommentary
Bibliographic record
Abstract
K Underhill Correspondence to: Ms K Underhill, University of Oxford, Oxford, UK; kristen.underhill@socres.ox.ac.uk Do sexual abstinence (SA) only programmes prevent HIV infection in high-income countries? ### Data sources: Medline, CINAHL, EMBASE/Excerpta Medica, CENTRAL, Catalogue of US Government Publications, and 25 other databases (1980 to February 2007); libraries of agencies involved with HIV prevention (eg, WHO); relevant conference proceedings (after 2000); experts; and cross-referencing articles on pregnancy prevention and HIV prevention. ### Study selection and assessment: randomised controlled trials (RCTs) or quasi-RCTs in any language that evaluated any intervention or programme for SA as the only means of HIV prevention in high-income countries (ie, gross national income/capita ⩾$10 726, £5450, or €8035). Trials of pregnancy and HIV prevention, or HIV prevention alone were included. Trials of people who were HIV positive, programmes explicitly promoting condom use or safe sex, SA only programmes not evaluating HIV prevention, and RCTs that did not report biological or behavioural …
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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 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".