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Record W2287252449 · doi:10.1126/science.aad5923

Violence and women's health

2015· editorial· en· W2287252449 on OpenAlexaboutno aff
Nancy E. Adler, Paula A. Johnson

Bibliographic record

VenueScience · 2015
Typeeditorial
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHarmQuarter (Canadian coin)Sexual assaultSexual violenceSuicide preventionOccupational safety and healthInjury preventionPoison controlEnvironmental healthDemographyHuman factors and ergonomicsMedicinePsychologyCriminologyGeographySocial psychologySociology

Abstract

fetched live from OpenAlex

Last month, the Association of American Universities' Campus Climate Survey provided a disturbing picture of the extent of sexual assault on campuses in the United States. Almost a quarter of female graduates surveyed from 27 institutions indicated having experienced sexual assault during their undergraduate period. Distressingly, violence on campuses is part of a larger epidemic of sexual violence in the United States, making it a major women's issue. The widespread prevalence of exposure to violence and its immediate harm and long-term health consequences argue for greater efforts in both research and treatment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.017
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.024
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0040.002
Science and technology studies0.0040.004
Scholarly communication0.0080.004
Open science0.0040.002
Research integrity0.0170.020
Insufficient payload (model declined to judge)0.0090.006

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 head0.029
GPT teacher head0.396
Teacher spread0.367 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEditorial

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

Citations9
Published2015
Admission routes1
Has abstractyes

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