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Record W2075881372 · doi:10.1300/j084v19n01_04

Detection and Prevalence of Abuse of Older Males: Perspectives from Family Practice

2007· article· en· W2075881372 on OpenAlex

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 Elder Abuse & Neglect · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsMcGill UniversitySt Mary's Hospital Centre
Fundersnot available
KeywordsElder abuseReferralMedicineOccupational safety and healthSuicide preventionPoison controlPsychiatryGerontologyFamily medicineMedical emergency

Abstract

fetched live from OpenAlex

Family doctors' frequent contact with seniors put them in reasonable positions to detect elder abuse and initiate referral to adult protective services. Since doctor reporting is low, however, this paper explores whether the gender of patient and/or doctor impacts on identification of elder mistreatment, or creates differential detection of one gender over the other. Use of the validated Elder Abuse Suspicion Index (EASI), and a structured social work evaluation, is described to provide some gender-based data from Canadian family practice. Specifically, while the prevalence of elder abuse is estimated to range from 12.0% to 13.3%, the specific prevalence was found for females to be 13.6% to 15.2% and for males 9.1% to 9.7%.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.308
Teacher spread0.293 · 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