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Record W3046677547 · doi:10.3390/ijerph17155607

Intimate Partner Violence: A Bibliometric Review of Literature

2020· review· en· W3046677547 on OpenAlexaboutno aff
Yanqi Wu, Jie Chen, Hui Fang, Yuehua Wan

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typereview
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational safety and healthHuman factors and ergonomicsPoison controlInjury preventionSuicide preventionDomestic violencePsychologyMedical emergencyMedicinePathology

Abstract

fetched live from OpenAlex

Intimate partner violence (IPV) is a worldwide public health problem. Here, a bibliometric analysis is performed to evaluate the publications in the Intimate Partner Violence (IPV) field from 2000 to 2019 based on the Science Citation Index (SCI) Expanded and the Social Sciences Citation Index (SSCI) databases. This work presents a detailed overview of IPV from aspects of types of articles, citations, h-indices, languages, years, journals, institutions, countries, and author keywords. The results show that the USA takes the leading position in this research field, followed by Canada and the U.K. The University of North Carolina has the most publications and Harvard University has the first place in terms of h-index. The London School of Hygiene and Tropical Medicine leads the list of average citations per paper. The Journal of Interpersonal Violence, Journal of Family Violence and Violence Against Women are the top three most productive journals in this field, and Psychology is the most frequently used subject category. Keywords analysis indicates that, in recent years, most research focuses on the research fields of “child abuse”, “pregnancy”, “HIV”, “dating violence”, “gender-based violence” and “adolescents”.

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)0.007
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score0.711

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.008
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.159
GPT teacher head0.507
Teacher spread0.348 · 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
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

Citations36
Published2020
Admission routes1
Has abstractyes

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