Medicalization of global health 2: the medicalization of global mental health
Bibliographic record
Abstract
Once an orphan field, 'global mental health' now has wide acknowledgement and prominence on the global health agenda. Increased recognition draws needed attention to individual suffering and the population impacts, but medicalizing global mental health produces a narrow view of the problems and solutions. Early framing by advocates of the global mental health problem emphasised biological disease, linked psychiatry with neurology, and reinforced categories of mental health disorders. Universality of biomedical concepts across culture is assumed in the globalisation of mental health but is strongly disputed by transcultural psychiatrists and anthropologists. Global mental health movement priorities take an individualised view, emphasising treatment and scale-up and neglecting social and structural determinants of health. To meet international targets and address the problem's broad social and cultural dimensions, the global mental health movement and advocates must develop more comprehensive strategies and include more diverse perspectives.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".