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Record W2983327137 · doi:10.22329/csw.v13i1.5847

An Exploration of Elder Abuse in a Rural Canadian Community

2019· article· en· W2983327137 on OpenAlexaffvenueabout
Megan MacKay-Barr, Rick Csiernik

Bibliographic record

VenueCritical Social Work · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsThe King's UniversityWindsor Regional Hospital
Fundersnot available
KeywordsEmbarrassmentElder abuseVerbal abuseMedicinePsychiatryRural areaPsychologySuicide preventionGerontologyPoison controlMedical emergencySocial psychology

Abstract

fetched live from OpenAlex

The Elder Abuse Awareness Committee of Chatham Kent, Ontario employed ten seniors (65 years of age or older) from this rural community to conduct an investigation of the knowledge and prevalence of elder abuse among their peers. The 236 study participants interviewed by the specifically trained elders were predominantly female ranging in age from 55 to over 90. The majority were still living in their own homes, had completed high school or post-secondary education, and reported relatively good health. These attributes predicted a rate of disclosed elder abuse within the lower end of the four to ten percent range typically reported in the literature. However, an incidence rate of 19.1% was reported nearly double the upper end of the range, with 137 separate acts of verbal, emotional, and financial abuse reported by participants to their peers. Formal paid caregivers were identified as the most frequent perpetrators though two thirds of the incidents were not reported to anyone at the time they occurred primarily due to embarrassment, fear, being dependent upon the abuser, or simply not knowing who to tell about the abuse. In the minority of instances when the abuse was reported the most common sources informed were the police, a family physician, or a helping professional in the community. 
 KEYWORDS: Elder abuse, rural, Canada

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 score0.442
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.057
GPT teacher head0.365
Teacher spread0.309 · 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

Citations4
Published2019
Admission routes3
Has abstractyes

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