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Record W3161866846 · doi:10.1177/10497315211010959

Preventing Harm to Vulnerable Older Adults: A Social Justice Perspective

2021· article· en· W3161866846 on OpenAlexaff
Joan Braun

Bibliographic record

VenueResearch on Social Work Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsLakehead University
Fundersnot available
KeywordsLegislationFocus groupSocial workHarmElder abuseQualitative researchStatutory lawGrounded theoryEconomic JusticeCriminologyPsychologyPublic relationsSocial psychologyNursingMedicineSociologyPolitical scienceLawPoison controlSuicide preventionEnvironmental health

Abstract

fetched live from OpenAlex

This article presents the results from a qualitative study that explored how legislation in British Columbia, intended to protect vulnerable adults from harm, is implemented in practice. The legislation contains guiding principles that require the least restrictive and minimally intrusive form of support or intervention be used and that the adult’s wishes be respected. Sixteen professionals who work as elder abuse responders in British Columba participated in this study through interviews and a focus group. Fifteen of the study participants were social workers. Grounded theory method was used, and themes were identified. The first theme reveals that responders prefer to obtain older adult consent to service provider involvement, rather than forcing compliance by using statutory authority. The second theme reveals that responders may not be able to intervene in a minimally intrusive manner because of resource shortages and organizational structural issues. These findings have human rights and social justice implications.

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)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0290.037
Scholarly communication0.0090.006
Open science0.0020.012
Research integrity0.0040.005
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 head0.139
GPT teacher head0.518
Teacher spread0.379 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations9
Published2021
Admission routes1
Has abstractyes

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