Health promotion, health promotion, where fore art though health promotion? The rise of the oxymoronic preventive health and the invisibilisation of health promotion
Bibliographic record
Abstract
The way we name things both shapes and reflects our feelings, judgements, choices and actions. Analyses of the changing discourse in health promotion highlight a major shift from the socially proactive health promotion first elucidated in 1986 in the Ottawa Charter for Health Promotion, to a more biomedically defensive form of health promotion. In this study, critical discourse analysis of 10 weight-related public health initiatives produced by the Australian Government between 2003 and 2013 revealed an almost complete backgrounding of the concept of health promotion, and a foregrounding of the concept of ‘preventive health’. This term draws on the biomedical concept of prevention but attempts to remove the disease connotation by coupling it with the term ‘health’. The resulting term is at best oxymoronic. The goal of preventive health is not to prevent health, but to prevent illness, injury, disease and death. The depoliticised ‘preventive health’ discourse is consistent with liberal and neo-corporatist ideology and a retreat of the welfare state. The consequence of such a shift in naming is to invisibilise or remove recognition from health promotion as a discipline and practice. This is personally and professionally confronting to us as health promotion practitioners and serves to devalue the principles of modern health promotion.; ;
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".