Bibliographic record
Abstract
The study uses logistic regression to examine how exposure to HIV/AIDS information in the mass media influences knowledge of the disease and risk behaviours in Ghana a West African country at a relatively early stage of the epidemic. It finds that mass media exposure increases awareness of partner fidelity condom use and avoidance of parenteral threats as ways of preventing infection and promotes condom use and partner fidelity as likely behavioural responses to the epidemic. Exposure to multiple channels reinforces media messages about safe sex and HIV/AIDS. Radio media seem to be the most powerful sources of information about the epidemic. They reach more people than television and print media and have larger effects on individuals knowledge base and behaviour. However the mass media influence has limits. Mass media exposure has no impacts on awareness and interest in abstinence and avoidance of commercial sex which means that they fail to address the needs of the poor women and the young who are the core sources of infection in the Ghanaian epidemic. I speculate that the structure of mass media effects observed may suggest that the national response to the campaign has been driven as much by political exigencies as by the logic of epidemiology. (authors)
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".