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Record W2070223550 · doi:10.1080/07399330701226438

Dating Violence and the Health of Young Women: A Feminist Narrative Study

2007· article· en· W2070223550 on OpenAlexaff
Farah Ismail, Hélène Berman, Catherine Ward‐Griffin

Bibliographic record

VenueHealth Care For Women International · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsWestern University
Fundersnot available
KeywordsDomestic violenceNarrativeExcusePsychologySuicide preventionPoison controlOccupational safety and healthPublic healthInjury preventionHealth careYoung adultHuman factors and ergonomicsSocial psychologyDevelopmental psychologyGender studiesMedicineSociologyNursingPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

Dating violence is a significant public health problem in the lives of young women. Their age, in conjunction with perceived pressures to engage in intimate relationships, makes these women particularly vulnerable to dating violence. The pressures to be in relationships can be intense and therefore may add to young women's willingness to overlook, forgive, or excuse the violence that is occurring. The authors' purposes in this feminist study were to examine the experience of dating violence from young women's perspectives; investigate how contextual factors shape their experiences; examine how health is shaped by these experiences; and explore ways that dating violence is perpetuated and normalized in young women's lives. Findings revealed that family environment and gender are critical in shaping young women's experiences. The participants described a range of physical and emotional health problems and perceived few sources of support. Their efforts to obtain support were often met with skeptical and dismissive attitudes on the part of health care providers and other trusted adults. Recommendations for health care practice, education, and research are presented.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.727

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.021
GPT teacher head0.397
Teacher spread0.377 · 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 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

Citations72
Published2007
Admission routes1
Has abstractyes

Explore more

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