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Record W1826158616 · doi:10.1177/0886260515584349

Intimate Partner Violence Among Pregnant Young Women

2015· article· en· W1826158616 on OpenAlexafffund
Sylvie Lévesque, Claire Chamberland

Bibliographic record

VenueJournal of Interpersonal Violence · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
FundersUniversité de Montréal
KeywordsDomestic violencePsychologyNonprobability samplingContext (archaeology)Psychological interventionPoison controlSuicide preventionHuman factors and ergonomicsInjury preventionDevelopmental psychologyOccupational safety and healthSocial psychologyMedicinePsychiatryPopulationMedical emergencyEnvironmental healthGeography

Abstract

fetched live from OpenAlex

This article explores intimate partner violence (IPV) as experienced by young women during the perinatal period. Using purposive sampling, data pertaining to the experiences of 10 young mothers were gathered through on-site participative observation and individual in-depth interviews. Interviews were coded in an inductive way to reflect the experiences of the participants before pregnancy and following pregnancy confirmation. Overall, the analyses of different manifestations of IPV and their contexts reveal the difficulty these young mothers experience in identifying themselves as a victim of IPV and in categorizing their partner's acts as intimate violence. The fear of family separation and the desire to protect their child contributed to the complexity of violence experienced in a context of motherhood. This article also reflects on the limits of data collection on this subject through comparison of the results of the interviews with the results of the Revised Conflict Tactics Scale (CTS-2). Further research is needed to provide more insight into victimization among young mothers and to inform interventions with the goal of helping young women overcome the intersecting challenges of violence and motherhood.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.319
Teacher spread0.290 · 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

Citations7
Published2015
Admission routes2
Has abstractyes

Explore more

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