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Record W2042582515 · doi:10.1080/08946566.2013.784085

A National Comparison of Spousal Abuse in Mid- and Old Age

2013· article· en· W2042582515 on OpenAlexaff
Yongjie Yon, Andrew Wister, Barbara Mitchell, Gloria Gutman

Bibliographic record

VenueJournal of Elder Abuse & Neglect · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsElder abuseLife course approachExploratory researchGerontologySuicide preventionPsychologyHuman factors and ergonomicsMedicineSituatedPoison controlClinical psychologyDemographyDevelopmental psychologyEnvironmental health

Abstract

fetched live from OpenAlex

This exploratory study addresses whether there are similar or different risks and protective factors associated with spousal abuse among mid-age adults (persons aged 45-59) and old-age adults (persons aged 60 and over). The risk and protective factors of abuse are compared across these two age groups and situated within a life course framework. Cross-sectional data from the 1999 and 2004 General Social Surveys are merged to address the research questions. Overall, it was found that there are as many differences as there are similarities in risk/protective factors connected to individual, relationship, and community environments. The findings are discussed in terms of program development and future research.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.029
GPT teacher head0.334
Teacher spread0.304 · 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 designObservational
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

Citations23
Published2013
Admission routes1
Has abstractyes

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