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Record W2524596148 · doi:10.1080/08946566.2016.1240053

State of the science on prevention of elder abuse and lessons learned from child abuse and domestic violence prevention: Toward a conceptual framework for research

2016· review· en· W2524596148 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.

Bibliographic record

VenueJournal of Elder Abuse & Neglect · 2016
Typereview
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversity of TorontoBaycrest Hospital
FundersNational Institute on Drug AbuseNational Institute of Mental HealthNational Institute on AgingNational Institutes of Health
KeywordsElder abuseDomestic violencePrevention sciencePsychologySuicide preventionPoison controlHuman factors and ergonomicsChild abuseConceptual frameworkInjury preventionOccupational safety and healthClinical psychologyPsychiatryMedicineMedical emergencySociologyIntervention (counseling)Social science

Abstract

fetched live from OpenAlex

The goal of this review is to discuss the state of the science in elder abuse prevention. Findings from evidence-based programs to reduce elder abuse are discussed, drawing from findings and insights from evidence-based programs for child maltreatment and domestic/intimate partner violence. A conceptual measurement model for the study of elder abuse is presented and linked to possible measures of risk factors and outcomes. Advances in neuroscience in child maltreatment and novel measurement strategies for outcome assessment are presented.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.173
GPT teacher head0.468
Teacher spread0.295 · 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