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Record W2004001525 · doi:10.1155/2014/801740

An Integrative Review of the Methods Used to Research the Prevalence of Violence against Women in Pakistan

2014· article· en· W2004001525 on OpenAlexaff
Farhana Madhani, Catherine Tompkins, Susan M. Jack, Anita Fisher

Bibliographic record

VenueAdvances in Nursing · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)PsychologyRigourDomestic violencePoison controlHuman factors and ergonomicsCriminologyApplied psychologyMedicineEnvironmental healthGeography

Abstract

fetched live from OpenAlex

This paper is a report of an integrative review conducted to assess the methodological and ethical strategies used to protect participants and researchers in conducting violence against women (VAW) studies in Pakistan. The measurement of the prevalence of violence against women in Pakistan is challenging for researchers given the cultural norms and the traditional role of women. Lack of methodological rigor in addressing the concerns can result in underreporting of violence, create physical and emotional risk for the participants, interviewers, and researchers, and impose threats to internal and external validity of VAW studies. Using Whittemore and Knafl’s process for conducting an integrative review, 11 studies published between 1999 and 2012, reporting on prevalence, experiences, and factors associated with violence in a marital relationship were analyzed. Overall, studies reveal an underreporting of exposure to violence and threats to women and interviewers’ safety in the conduct of such studies, both of which present threats to study rigor. The utilization of WHO ethical and safety recommendations to guide VAW studies in this context should be considered.

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)0.012
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.538
Teacher spread0.492 · 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 designOther design
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

Citations6
Published2014
Admission routes1
Has abstractyes

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