MétaCan
Menu
Back to cohort

Mad by the Millions

2021· book· en· W4246015138 on OpenAlexfundno aff
Harry Yi‐Jui Wu

Bibliographic record

VenueThe MIT Press eBooks · 2021
Typebook
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsnot available
FundersChiang Ching-Kuo Foundation for International Scholarly ExchangeWellcome TrustMcGill University
KeywordsPsycheMental healthSociologyPolitical sciencePublic relationsSocial sciencePsychologyPsychiatryPsychoanalysis

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.075
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.069
GPT teacher head0.355
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations27
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueThe MIT Press eBooksSame topicMental Health Treatment and AccessFrench-language works237,207