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Record W1560133960 · doi:10.3138/cbmh.24.1.67

“Their Lack of Masculine Security and Aggression Was Obvious”: Gender and the Medicalization of Inebriety in the United States, 1930–50

2007· article· en· W1560133960 on OpenAlexvenueno aff
Stephen Patnode

Bibliographic record

VenueCanadian Journal of Health History · 2007
Typearticle
Languageen
FieldPsychology
TopicHistorical Psychiatry and Medical Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicalizationHuman sexualityVisionGender studiesHumanitiesCriminologySociologyPsychiatryEthnologyMedicineArtAnthropology

Abstract

fetched live from OpenAlex

This article examines the roles of gender and sexuality in the public and private debate over medicalizing inebriety in the United States from 1930-50. During this period various interest groups wrestled with two competing visions of how to frame chronic drinking, which came to be labelled alcoholism following the repeal of Prohibition. Mainstream doctors and psychiatrists agreed that the underlying cause of alcoholism was in the mind of the individual. A number of psychiatrists went further, suggesting a connection between alcoholism and latent homosexuality. In contrast, laypeople identifying themselves as alcoholics advanced a second, competing vision of alcoholism that framed it as a blameless physiological illness. This second understanding of alcoholism, particularly as promoted by members of Alcoholics Anonymous (AA), emphasized the need for restoring heteronormative gender roles for alcoholics (who were generally men) and their spouses (who were generally women) as an important step to recovery. Indeed, this may help to explain the success of AA and its medicalization model in the US from 1930-50, as both built upon widely held cultural assumptions concerning gender roles and sexuality.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score0.562

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.014
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0020.004
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 head0.071
GPT teacher head0.348
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Health HistorySame topicHistorical Psychiatry and Medical PracticesFrench-language works237,207