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Record W2603297287 · doi:10.3138/jcfs.40.1.47

Perspectives on Elder Abuse in Korea

2009· article· en· W2603297287 on OpenAlexvenueno aff
Mikyung Jang

Bibliographic record

VenueJournal of Comparative Family Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
Fundersnot available
KeywordsElder abuseNeglectPsychological abuseImprisonmentPhysical abusePsychologyVerbal abuseChild abusePsychiatryClinical psychologySuicide preventionMedicinePoison controlCriminologyMedical emergency

Abstract

fetched live from OpenAlex

Although social interest in elder maltreatment is increasing in Korea, the actual prevalence of elder abuse is hard to determine, and it is not even clear how “elder abuse” is generally defined. In particular, little is known about how aging adults are treated at home or in facilities or to what extent and under what circumstances their treatment might be considered abusive. In this study, a convenience sample of 102 Korean undergraduate students completed an open-ended qualitative survey asking them to provide examples, in their own words, of extreme, moderate, and mild abuse in family relationships. When giving examples of extreme elder abuse, these students emphasized neglect and physical maltreatment, followed by imprisonment and verbal abuse. When giving examples of moderate and mild elder abuse, respondents most frequently mentioned various forms of neglect and psychological abuse. Neglect, physical abuse, imprisonment, and sending the elderly to an institution were reported significantly more often as examples of extreme abuse than of moderate or mild abuse. In addition, Korean women tended to focus more on neglect than Korean men when giving examples of extreme elder abuse, whereas Korean men focused more on neglect than Korean women when giving examples of mild 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.

How this classification was reachedexpand

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.124
GPT teacher head0.431
Teacher spread0.306 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations6
Published2009
Admission routes1
Has abstractyes

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