A Newspaper Content Analysis of HIV/AIDS and Food Insecurity in Sub‐Saharan Africa
Bibliographic record
Abstract
Abstract This study sought to identify media links presented between food insecurity and the HIV pandemic in sub‐Saharan Africa through description of commonly portrayed frames found in high visibility Western and African print media sources. An episodic sampling process during the summer of 2006 found articles that tied food security to the HIV pandemic. Content analysis employed a mixed methodology grounded in naturalistic inquiry. Included were interpretative thematic analyses of text and images along with a frequency content coding instrument as a means of triangulation. Several themes emerged during analysis of the sample, including a biomedical frame, war and competition imagery, economic threats, food insecurity as a contributing factor for HIV infection, and hopeful action. Differences noted within Western and African print media framing of food security within the HIV pandemic consisted of an overall Western portrayal that was less actionable and more hopeless in nature than African portrayals. The potential of integrating existing frames and working towards newer frames is discussed as a method to improve citizen‐level action on global issues and further the agenda‐setting process necessary for policy development.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".