An assessment of global Internet-based HIV/AIDS media coverage: implications for United Nations Programme on HIV/AIDS' Global Media HIV/AIDS Initiative
Bibliographic record
Abstract
No studies to date have assessed the quantity of HIV/AIDS-related media on the Internet. We assessed the quantity of language-specific HIV/AIDS Internet-based news coverage, and the correlation between country-specific HIV/AIDS news coverage and HIV/AIDS prevalence. Internet-based HIV/AIDS news articles were queried from Google News Archives for 168 countries, for the year 2007, in the nine most commonly spoken languages worldwide. English, French and Spanish sources had the greatest number of HIV/AIDS-related articles, representing 134,000 (0.70%), 11,200 (0.65%) and 24,300 (0.49%) of all news articles, respectively. A strong association between country-specific HIV/AIDS news coverage and HIV/AIDS prevalence was found, Spearman's rank correlation: 0.6 (P < 0.001). Among countries with elevated HIV/AIDS prevalence (> or =10%), the volume of HIV/AIDS-specific media was highest in Swaziland (15.9%) and Malawi (13.2%), and lowest in South Africa (4.8%) and Namibia (4.9%). Increased media attention should be placed on countries with high HIV/AIDS prevalence and limited HIV/AIDS-specific news coverage.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".