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Record W2138725257 · doi:10.3109/09540261.2010.506184

Culture and the social construction of gender: Mapping the intersection with mental health

2010· review· en· W2138725257 on OpenAlexaff
Lisa Andermann

Bibliographic record

VenueInternational Review of Psychiatry · 2010
Typereview
Languageen
FieldMedicine
TopicSex and Gender in Healthcare
Canadian institutionsUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsMental healthPsychologyNegotiationGlobal mental healthMiddle Eastern Mental Health Issues & SyndromesQualitative researchGender studiesSocial psychologySociologyMental health lawSocial sciencePsychiatry

Abstract

fetched live from OpenAlex

The social construction of gender is an important concept for better understanding the determinants of mental health in women and men. Going beyond physical and physiological differences and the traditional biomedical approach, interdisciplinary study of the complex factors related to culture and society, power and politics is necessary to be able to find solutions to situations of disparity in mental health, related to both prevalence of disorders, availability and response to treatment. Gender inequality continues to be a source of suffering for many women around the world, and this can lead to adverse mental health outcomes. This review focuses on developments in the literature on culture, gender and mental health over the past decade, focusing on themes around the social construction of gender, mental health and the media, a look at cultural competence through a gender lens, gender and the body, providing some examples of the intersection between mental health and gender in low-income countries as well as the more developed world, and the impact of migration and resettlement on mental health. At the clinical level, using a bio-psycho-social-spiritual model that can integrate and negotiate between both traditional and biomedical perspectives is necessary, combined with use of a cultural formulation that takes gender identity into account. Research involving both qualitative and quantitative perspectives, and in many cases an ethnographic framework, is essential in tackling these global issues.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.362

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.062
GPT teacher head0.406
Teacher spread0.344 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2010
Admission routes1
Has abstractyes

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