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Record W330684565 · doi:10.1177/003335491012500517

Is Impairment in Physical Function Associated with Increased Risk of Elder MistreatMent? Findings from a Community-Dwelling Chinese Population

2010· article· en· W330684565 on OpenAlexaboutno aff
Mark Robson, XinQi Dong, Melissa A. Simon

Bibliographic record

VenuePublic Health Reports · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
FundersNational Center for Research ResourcesNational Institute on Aging
KeywordsChinaChinese populationPublic healthGerontologyPopulationQuarter (Canadian coin)Function (biology)Chinese cultureChinese americansMedicineSociologyEnvironmental healthPolitical scienceGeographyEthnic group

Abstract

fetched live from OpenAlex

This article by Dong and Simon provides us with unique insight into mistreatment of the elderly as both a human rights issue and a public health issue.Chinese culture and customs are not well-known to many people; however, in less than four decades, one-quarter of the world's elderly population will be Chinese.There is a strong bond within Chinese families that spans generations.This bond is being tested and, in many cases, disrupted with the rapid economic changes in China, the new mobility of rural populations, and the influence of Western culture on Chinese culture.Dong and Simon have completed the first study of the aging Chinese population to examine the association of elder mistreatment and physical function.The metrics and measures used in this study can also translate into other cultures around the global with the same challenges.Despite its limitations, this study provides a starting point for examining this important global public health issue.

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 score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.026
GPT teacher head0.326
Teacher spread0.299 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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