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Domestic Violence against Women and COVID-19 Quarantine: ASystematic Review Study

2023· review· en· W4321455819 on OpenAlexaboutno aff
Seideh-Hanieh Alamolhoda, Elham Zare, Mahbobeh Ahmadi Doulabi, Parvaneh Mirabi

Bibliographic record

VenueCurrent Women s Health Reviews · 2023
Typereview
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsScopusDomestic violenceCoronavirus disease 2019 (COVID-19)MEDLINEQuarantineWeb of scienceMedicineInclusion (mineral)PandemicPoison controlSuicide preventionFamily medicinePsychiatryPsychologyEnvironmental healthMeta-analysisPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

Background: Domestic violence against women is defined as physical, sexual, and emotional abuse, that women experience. During the COVID-19 quarantine, homes have become very dangerous places for domestic violence against women. Methods: Following PRISMA guidelines, Medline, Scopus, Embase, Google scholar, and web of science were searched. Two independent authors screened all identified titles, abstracts, and relevant full texts for inclusion in the systematic review. 7 primary studies that were published between December 2019 and March 2021 were examined. The risk of bias in the retrieved articles was assessed by the Newcastle–Ottawa Scale. Results: During the COVID-19 lockdown, people have experienced different situations that lead to increasing aggressive behavior with possible trauma and violence, especially against women. Conclusion: During the quarantine of the COVID-19 pandemic around the world, we need programs aimed at preventing acts of domestic violence against women, such as trained multi-disciplinary staff, including psychologists, sexologists, and clinical psychiatrists.

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)0.032
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0320.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.003

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 head0.259
GPT teacher head0.542
Teacher spread0.283 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

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