Manufacturing Consent?: Media Messages in the Mobilization Against HIV/AIDS in India and Lessons for Health Communication
Bibliographic record
Abstract
Despite repeated calls for a more critical and "culture-centered" approach to health communication, textual analysis of televised public service advertising (PSA) campaigns has been largely neglected, even by critical communication scholars. In the case of "developing" countries in particular, there is an acute shortage of such literature. On the other hand, following the outbreak of major public health diseases such as AIDS, most countries have adopted PSA campaigns as the most preferred means of communicating messages. Drawing on insights from cultural studies (especially Antonio Gramsci and Stuart Hall), this article engages in textual analysis of the televised PSA campaigns launched by the Indian state to prevent HIV/AIDS between 2002 and 2005. Through such analysis, it argues that although few diseases in Indian history have spurred such massive and creative efforts for mass mobilization as AIDS, these efforts, in terms of their ethical implications, have been far from emancipatory. In fact, they have constructed and perpetuated the logic of domination and control along class, gender, sexuality, and knowledge systems, often contradicting and potentially harming the very goal of HIV prevention and of health promotion and empowerment. This article also holds that assessing public health campaigns through textual analysis, a highly neglected tool in health communication, can shed important light on a far more complex and changing nature of the state and public policy, especially in the developing world, thereby opening up space for alternative theorizing for health communication and social change.
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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.037 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".