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Intimate partner violence among speaking immigrant adult Portuguese women in Canada

2016· article· en· W2588038882 on OpenAlexaffabout
Rafaella Queiroga Souto, Sepali Guruge, Míriam Aparecida Barbosa Merighi, María Jesús, Shaindel Egit, Linda Kiernan Knowles

Bibliographic record

VenueRevista da Escola de Enfermagem da USP · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPortugueseFeelingDomestic violenceImmigrationPsychologySuicide preventionHealth careSocial psychologyGender studiesPoison controlMedicineSociologyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: This study was conducted to understand the experiences of intimate partner violence among women from Portuguese-speaking countries living in the Greater Toronto Area. METHOD: A social phenomenological study was conducted with ten Portuguese-speaking women who had experienced intimate partner violence who were selected by community centre leaders. The interviews were transcribed, translated and analysed by categories. RESULTS: The consequences of violence included health problems, effects on children, and negative feelings among the victims. Factors preventing the women from leaving abusive partners included religious beliefs, challenging daily jobs, and the need to take care of their husband. Factors that encouraged them to leave included getting support and calling the police. Some women expressed hope for the future either with their husband. Others, desired divorce or revenge. Their plans to rebuild their lives without their husband included being happy, learning English, and being financially stable. CONCLUSION: Using these findings can implicate in the improvement of care for these women.

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)0.000
metaresearch head score (Gemma)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.296
Teacher spread0.276 · 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

Citations10
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueRevista da Escola de Enfermagem da USPSame topicIntimate Partner and Family ViolenceFrench-language works237,207