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Record W2613405126

선진국 노인학대 지원제도 및 프로그램 비교연구 - 미국 , 캐나다 , 영국 , 일본을 중심으로 -

2001· article· ko· W2613405126 on OpenAlexaboutno aff
이연호

Bibliographic record

Venue노인복지연구 · 2001
Typearticle
Languageko
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
Fundersnot available
KeywordsElder abuseLegislationAgency (philosophy)Context (archaeology)Social supportSocial workPublic relationsPolitical sciencePsychologyMedicinePoison controlSuicide preventionEnvironmental healthSociologySocial psychologyLawGeographySocial science
DOInot available

Abstract

fetched live from OpenAlex

The multifaceted nature of elder abuse issue, which involve social, legal, and environmental matters, requires that action take place on the social and legal levels and that it involve multiple system The purpose of this study is to ermine and compare the support system and program of elder abuse in the advanced industrial countries : USA, Canada, United Kingdom, Japan in order to reduce trial and error and consider the successful social support system and program for elder abuse in Korean context. To this end, this study focuses on comparaing three major aspects of support system and program of elder abuse in four advanced industrial countries : the prevalence and incidence of elder abuse, the definition of the term elder abuse and types, and the available social support system and services. Especially, the aspect of social support system and program was divided into three aspects again : the legislation and regulation, the organization and agency, and programs and services of elder abuse. Finally, on the basis of these comparative analysis, this study discussed and recommended the future direction of social support system and program of elder abuse in Korean conte.

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 score0.991
Threshold uncertainty score0.019

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)0.0020.000

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 head0.030
GPT teacher head0.315
Teacher spread0.285 · 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

Citations0
Published2001
Admission routes1
Has abstractyes

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