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Record W2792686786 · doi:10.1177/0886260518764384

Social Structure, Social Learning, and the Severity of Physical Intimate Partner Violence Against Women in Nigeria

2018· article· en· W2792686786 on OpenAlexaff
Emeka Eugene Dim, Patience Elabor-Idemudia

Bibliographic record

VenueJournal of Interpersonal Violence · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDomestic violencePoison controlPsychologySuicide preventionPhysical abuseContext (archaeology)Developmental psychologyHuman factors and ergonomicsInjury preventionOccupational safety and healthSocial environmentSocial psychologyMedicineEnvironmental healthSociologyGeography

Abstract

fetched live from OpenAlex

Using the Nigerian Demographic and Health Survey (NDHS) of 2013, this study applies the social structure (feminist) and social learning perspective in understanding the severity of physical intimate partner violence (IPV) in Nigeria. About 26,403 married women were analyzed from the 2013 NDHS data. Multinomial regression was used to analyze variables that capture the social structural and social learning perspectives in relation to women's experience of minor and severe physical IPV. The study revealed that primary and secondary educational attainment, and being employed predicted severe physical IPV victimization. Alcohol consumption by the respondents' spouses, being a victim of childhood abuse, and witnessing IPV between parents predicted severe physical IPV. The finding of this study implies that experiences of IPV take place within a sociocultural context that shapes the social realities of the average Nigerian woman.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
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 head0.012
GPT teacher head0.324
Teacher spread0.312 · 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.

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

Citations18
Published2018
Admission routes1
Has abstractyes

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