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Record W4403459021 · doi:10.3390/soc14100205

Gender-Based Violence in the Context of Mothering: A Critical Canadian Health Perspective

2024· article· en· W4403459021 on OpenAlexaffabout
Tara Mantler, Kimberley T. Jackson

Bibliographic record

VenueSocieties · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsWestern University
Fundersnot available
KeywordsPerspective (graphical)Context (archaeology)PsychologySociologyGender studiesDevelopmental psychologyGeographyComputer science

Abstract

fetched live from OpenAlex

Violence against women is a predominant, human rights violation, globally. Understood as any act of gender-based violence resulting in physical, sexual, or psychological harm or suffering to women, approximately 35% of women experience violence across the lifespan. While violence can be experienced at any age, women of reproductive age suffer the greatest prevalence, underscoring that for many women, experiencing violence or the health and social sequelae, which may follow violence, co-occurs with mothering. Mothering in the context of gender-based violence in Canada is complex and multifaceted. In this article, the interplay among gender-based violence and the childbearing stages of pregnancy, birth, and postpartum are explored using an intersectional lens, including consideration of social disparities and equity-deserving groups. Approaches to address gender-based violence among childbearing women, such as an ecological approach and trauma- and violence-informed care, are discussed as implications for further research and practice.

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)0.007
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.193
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0460.038
Scholarly communication0.0150.006
Open science0.0040.009
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0060.000

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 head0.056
GPT teacher head0.389
Teacher spread0.333 · 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

Citations4
Published2024
Admission routes2
Has abstractyes

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