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Record W2311480124 · doi:10.1136/medhum-2015-010734

Gendering psychosis: the illness of Zelda Fitzgerald

2015· article· en· W2311480124 on OpenAlexaff
Mary V. Seeman

Bibliographic record

VenueMedical Humanities · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicAmerican and British Literature Analysis
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsPsychosisPsychologyAgency (philosophy)CreativityBiographyIntellectPsychiatryPsychoanalysisDevelopmental psychologySocial psychologySociologyHistoryEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

Psychiatric textbooks tend to describe psychosis as it is experienced by men. The well-documented illness of Zelda Fitzgerald illustrates the feminine side of psychosis. The distinctive features of Zelda's illness--its specific precipitants, the timing of its onset, the discontinuities in its course, the pronounced mood swings, the preservation of intellect and of agency, the maintenance of human ties, the association of flare-ups with immune and hormonal changes, the responsiveness to treatment, the lifelong creativity and productivity--show the female side of psychotic illness, one that is rarely described in diagnostic manuals. This paper relies on Nancy Milford's biography of Zelda, as well as on several other biographical sources and, using Zelda's own words and the words of her husband and friends, allows entry into a feminine world of psychosis, not encountered in textbooks. The expression of psychotic illness varies from person to person, its exact shape depending on many factors, most of them still undetermined, but gender is a critically important core component of variance.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.002
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 head0.053
GPT teacher head0.247
Teacher spread0.194 · 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 designNot applicable
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

Citations9
Published2015
Admission routes1
Has abstractyes

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