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Record W2961456158 · doi:10.1002/jid.3430

Socio‐economic Status, Demographic Characteristics and Intimate Partner Violence

2019· article· en· W2961456158 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of International Development · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsDomestic violenceRespondentSocioeconomic statusQuarter (Canadian coin)DemographyDemographic economicsPsychologySocioeconomicsHuman factors and ergonomicsPoison controlGeographyEconomicsEnvironmental healthSociologyPolitical scienceMedicinePopulation

Abstract

fetched live from OpenAlex

Abstract One in three ever‐partnered women worldwide has experienced intimate partner violence (IPV), yet there is little systematic global evidence on the association between socio‐economic status (SES), demographic characteristics and IPV. This paper uses information from more than one‐quarter of one million female respondents age 15–49 in IPV modules from 36 Demographic and Health Surveys to provide detailed evidence on IPV gradients around the developing world. The analysis reveals relatively large negative IPV–SES gradients for respondent years of schooling and household wealth. Marriage and higher age are generally associated with lower IPV, whereas the physical violence–age profile follows an inverted U‐shape. © 2019 John Wiley & Sons, Ltd.

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.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.474

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.014
GPT teacher head0.298
Teacher spread0.284 · 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