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Record W2143317770 · doi:10.1177/088626000015003002

Minimizing Negative Experiences

2000· article· en· W2143317770 on OpenAlex
Katherine Dunham, Charlene Y. Senn

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Interpersonal Violence · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPhenomenonLogistic regressionPsychologyHuman factors and ergonomicsPoison controlSocial psychologyClinical psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

Women who have experienced abuse in intimate relationships often omit information about the abuse when disclosing to others. Data describing this phenomenon have been anecdotal and concerned only with disclosures to clinicians and social scientists. This study documented the prevalence of minimization in disclosures to friends and relatives and explored factors that might predict minimization. The results revealed that 36.1% of women who disclosed abuse to friends and relatives omitted information. A stepwise logistic regression indicated increased severity of abuse, more accepting attitudes toward physical abuse, and delayed disclosure were each positively associated with minimization. We tentatively suggest that this phenomenon can be viewed as an attempt to manage confidants' reactions to disclosure of abuse and enhance the likelihood of social support. Whether providing an incomplete picture of the situation serves to facilitate or undermine the quality of social support received is an empirical question that must be explored.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.323
Teacher spread0.303 · 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