MétaCan
Menu
Back to cohort
Record W2005111471 · doi:10.1177/088626000015006001

Aggregation Bias and Woman Abuse

2000· article· en· W2005111471 on OpenAlex
Martin D. Schwartz, Walter S. DeKeseredy

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Interpersonal Violence · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicIntimate Partner and Family Violence
Canadian institutionsCarleton University
Fundersnot available
KeywordsVariety (cybernetics)Affect (linguistics)PsychologySexual abusePopulationHuman factors and ergonomicsSocial psychologyPoison controlDemographyMedicineClinical psychologyCriminologySociologyMedical emergency

Abstract

fetched live from OpenAlex

Many researchers have been attracted to broad, national-level surveys as an antidote to the more usual practice of studying woman abuse in one location or campus and presuming that the results generalize to the entire population. However, the reverse error is also possible: presuming that one national rate may adequately represent a variety of different regions, types of schools, and cultural groups. This article analyzes the Canadian National Survey data to compare geographic regions, types of schools, and whether the students took the survey in French or English. None of these factors influenced the results. Male peer support measures, as hypothesized, did strongly affect male behavior in both physical and sexual abuse.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.748

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.310
Teacher spread0.284 · 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