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Record W3168570661

A Feminist Science Commentary: A Socially Cognizant Analysis of Postpartum Depression in the Western World

2021· article· en· W3168570661 on OpenAlexvenueno aff
Imaan Zera Kherani

Bibliographic record

VenueUniversity of Toronto Medical Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
Fundersnot available
KeywordsMedicalizationDeviance (statistics)ObjectificationSociologyShameChildbirthPsychologyPostpartum depressionGender studiesDevelopmental psychologySocial psychologyPsychiatryPolitical science
DOInot available

Abstract

fetched live from OpenAlex

In Western and Eurocentric literature, postpartum depression (PPD) has been explored through medical and psychosocial lenses highlighting the inextricable social nature of the illness experience. Using a feminist theory analysis lens, this paper urges for critical consideration of the social requirements and cultural expectations that the mother and newborn exist within. This analysis explores the medicalization of childbirth, the conception of flawless motherhood, and the perceived deviance from feminine gender scripts as prudent risk factors to consider in the development of PPD. The medicalization of childbirth is characterized with rigidity, loss of maternal agency, and an external locus of control compounded by system strain. Widespread, Western constructs of maternal perfection and excellence create a dissonance for new mothers between idealistic motherhood and experienced reality, generating low maternal esteem and isolation. Finally, depression experienced amidst motherhood has been considered deviant from the classic, Western feminine gender script, generating maternal shame and guilt. The feminist analysis of PPD lends itself towards a socially cognizant analysis that acknowledges social priorities and expectations that leave new mothers suffering in isolation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.298
Teacher spread0.282 · 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 designObservational
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 routes1
Has abstractyes

Explore more

Same venueUniversity of Toronto Medical JournalSame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207