MétaCan
Menu
Back to cohort
Record W3200143582 · doi:10.1093/jhmas/jrab039

Quantifying Sexual Constitution: Abraham Myerson's Endocrine Study of Male Homosexuality, 1938-1942

2021· article· en· W3200143582 on OpenAlexafffund
Matthew McLaughlin

Bibliographic record

VenueJournal of the History of Medicine and Allied Sciences · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsHomosexualityHuman sexualityPsychologyFemininityPsychoanalysisGender studiesSociology

Abstract

fetched live from OpenAlex

Using the new medical science of endocrinology, scientific sex researchers in the 1920s and 1930s began studying sex hormone excretion as a means to search for the biological basis of human sexuality. One of these researchers was Abraham Myerson, a leading psychiatrist and researcher from Boston who conducted a series of innovative endocrine experiments between 1938 and 1942 in an effort to establish a relationship between sex hormone excretion patterns and homosexuality in men. While prevailing cultural models of heteronormativity identified male homosexuality as an abnormal case of biological femininity in men, Myerson's framework and experimental research transcended this limiting duality of sexual biology. Adopting the theory of bisexuality, he argued that all men possessed a natural variability of masculine and feminine traits in their biological, social, and sexual characteristics, and that the disparity among these traits could be quantified and understood using sex hormones. In reconstructing Myerson's research methods and data analysis, this paper uncovers how he established a distinctive diagnostic method and classification system for male homosexuality and illuminates how he conceptualized and categorized male sexuality as quantifiable and independent of personality.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.288
GPT teacher head0.343
Teacher spread0.055 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the History of Medicine and Allied SciencesSame topicHistorical Studies on Reproduction, Gender, Health, and Societal ChangesFrench-language works237,207