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Record W2162780702 · doi:10.1136/ebn.3.2.60

Women had an inherent sense of<i>knowing how</i>to manage their lives after sexual assault by men they knew

2000· article· en· W2162780702 on OpenAlexaff
Colleen Varcoe

Bibliographic record

VenueEvidence-Based Nursing · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMedicinePsychologySexual violenceNeglectCoping (psychology)Web of scienceGynecologyPsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

Draucker CB. Knowing what to do: coping with sexual violence by male intimates. Qual Health Res1999 Sep; 9 : 588 –601 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: What is the meaning of sexual violence in the lives of women who have been sexually assaulted by men they knew well? Heideggerian hermeneutics. Northwestern Ohio, USA. 10 women >18 years of age (age range 19-57 y, 8 white, 2 African-American) who had been sexually assaulted as adults by men they knew well were recruited by public announcements. 7 of the women had experienced childhood abuse or neglect, and many had several abusive relationships as adults. 1–3 hour interviews were held with each woman and began with open ended questions about the meaning of the experience of sexual violence and how it affected their day to day lives. The author and another psychiatric nurse independently reviewed the interview transcripts, prepared written interpretations, and discussed and compared the interpretations. A qualitative research group also reviewed selected transcripts and commented on the emerging themes. 5 … [1]: {openurl}?query=rft.jtitle%253DQualitative%2BHealth%2BResearch%26rft.stitle%253DQual%2BHealth%2BRes%26rft.aulast%253DDraucker%26rft.auinit1%253DC.%2BB.%26rft.volume%253D9%26rft.issue%253D5%26rft.spage%253D588%26rft.epage%253D601%26rft.atitle%253DKnowing%2BWhat%2Bto%2BDo%253A%2BCoping%2Bwith%2BSexual%2BViolence%2Bby%2BMale%2BIntimates%26rft_id%253Dinfo%253Adoi%252F10.1177%252F104973299129122108%26rft_id%253Dinfo%253Apmid%252F10558369%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1177/104973299129122108&link_type=DOI [3]: /lookup/external-ref?access_num=10558369&link_type=MED&atom=%2Febnurs%2F3%2F2%2F60.atom [4]: /lookup/external-ref?access_num=000081930400003&link_type=ISI

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)0.003
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.048
GPT teacher head0.310
Teacher spread0.262 · 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
GenreEmpirical

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

Citations1
Published2000
Admission routes1
Has abstractyes

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