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Record W4390340284 · doi:10.36922/ijps.376

Gender symmetry: A systematic review of men’s experiences of intimate partner violence during COVID-19 pandemic lockdown

2023· review· en· W4390340284 on OpenAlexfundno aff
Dorothy N. Ononokpono, Endurance Uzobo

Bibliographic record

VenueInternational Journal of Population Studies · 2023
Typereview
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
FundersNational Research FoundationInternational Development Research CentreUK Research and InnovationStyrelsen för Internationellt Utvecklingssamarbete
KeywordsPandemicDomestic violenceSystematic reviewCoronavirus disease 2019 (COVID-19)Grey literaturePsychologyPublic healthPoison controlSuicide preventionMEDLINEMedicineCriminologyPolitical scienceMedical emergencyNursingInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

Intimate partner violence (IPV) is a public health concern. However, men’s experiences of IPV have been largely neglected in previous studies. This systematic review aimed to examine men’s experiences of IPV during the COVID-19 pandemic lockdown. Six online bibliographic databases were used to identify relevant published peer-reviewed journal articles and gray literature. A total of 19 journal articles and gray literature that examined the prevalence, types, and consequences of violence experienced by men during the COVID-19 pandemic lockdown were extracted for review. This systematic review is anchored on the gender symmetry theory developed by Straus and Gelles. Expectedly, females were the major victims of IPV cases, but a significant number of men around the world also experienced IPV during the COVID-19 pandemic lockdown. This finding suggests that evidence-based approaches that also recognize men as victims of IPV should be taken into account for minimizing such cases.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
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 head0.228
GPT teacher head0.509
Teacher spread0.281 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations4
Published2023
Admission routes1
Has abstractyes

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