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Record W1971607211 · doi:10.1177/1363459313476965

Surviving men’s depression: Women partners’ perspectives

2013· article· en· W1971607211 on OpenAlexafffund
Joan L. Bottorff, John L. Oliffe, Mary T. Kelly, Joy L. Johnson, Joanne Carey

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General HospitalUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsFemininityDepression (economics)PsychologyContext (archaeology)Doing genderMasculinitySocial psychology

Abstract

fetched live from OpenAlex

While men's gendered experiences of depression have been described, the perspectives of women partners who are affected by men's depression have received little attention. Women partners were recruited to explore how men's depression impacts them and its influence on gender regimes. Individual interviews with 29 women spouses were coded and analysed. Although idealized femininity positions women as endlessly patient and caring, our findings reveal significant challenges in attempting to fulfil these gender ideals in the context of living with a male partner who is experiencing depression. The strain and drain of living with a depressed man was a key element of women's experiences. Four sub-themes were identified: (1) resisting the emotional caregiver role, (2) shouldering family responsibilities, (3) connecting men to professional care and (4) preserving the feminine self. The findings suggest that men's depression has great potential to dislocate heterosexual gender regimes, and attention to gender relations should be included to ensure successful care management of men who experience depression.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.003
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.080
GPT teacher head0.480
Teacher spread0.401 · 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

Citations25
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueHealth An Interdisciplinary Journal for the Social Study of Health Illness and MedicineSame topicGender Roles and Identity StudiesFrench-language works237,207