Bibliographic record
Abstract
The World Health Organization's post–World War II work on the epidemiology and classification of mental disorders and its vision of a “world psyche.” In 1948, the World Health Organization began to prepare its social psychiatry project, which aimed to discover the epidemiology and arrive at a classification of mental disorders. In Mad by the Millions, Harry Y-Jui Wu examines the WHO's ambitious project, arguing that it was shaped by the postwar faith in technology and expertise and the universalizing vision of a “world psyche.” Wu shows that the WHO's idealized scientific internationalism laid the foundations for today's highly metricalized global mental health system. Examining the interactions between the WHO and developing countries, Wu offers an analysis of the “transnationality” of mental health. He examines knowledge-sharing between the organization and African and Latin American collaborators, and looks in detail at the WHO's selection of a Taiwanese scientist, Tsung-yi Lin, to be its medical officer and head of the social psychiatry project. He discusses scientists' pursuit of standardization—not only to synchronize sectors in the organization but also to produce a common language of psychiatry—and how technological advances supported this. Wu considers why the optimism and idealism of the social psychiatry project turned to dissatisfaction, reappraising the WHO's early knowledge production modality through the concept of an “export processing zone.” Finally, he looks at the WHO's project in light of current debates over psychiatry and global mental health, as scientists shift their concerns from the creation of universal metrics to the importance of local matrixes.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.182 | 0.053 |
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".