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Sexual Harassment: Everyday Violence in the Lives of Girls and Women

2000· review· en· W2327337281 on OpenAlexaffabout
Hélène Berman, Katherine McKenna, Carrie Traher Arnold, Gail Taylor, Barbara J. MacQuarrie

Bibliographic record

VenueAdvances in Nursing Science · 2000
Typereview
Languageen
FieldSocial Sciences
TopicSexual Assault and Victimization Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsHarassmentGirlPsychologyAllianceSexual violencePopulationResistance (ecology)Poison controlDevelopmental psychologySocial psychologyCriminologyPolitical scienceSociologyMedicineDemographyMedical emergency

Abstract

fetched live from OpenAlex

Sexual harassment is one of the most insidious, yet pervasive, forms of violence that affects all girls, not merely those traditionally thought to be vulnerable or at risk. Although harassment in the workplace has been the focus of considerable attention during the last decade, there is a growing recognition that girls experience varied forms of sexual harassment, and that this behavior begins at a surprisingly early age. This article examines the plight of the "girl child" and presents findings from the first phase of a national action research project currently being conducted by the Canadian Alliance of Five Research Centres on Violence. A major objective of this project is to examine how violence becomes "normalized" in the lives of girls and young women. Implications for nurses, including strategies aimed at encouraging resistance among this population, are addressed.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.432
Teacher spread0.398 · 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 designQualitative
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

Citations53
Published2000
Admission routes2
Has abstractyes

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