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Record W3100760286 · doi:10.1108/jap-08-2020-0034

COVID-19 and residential care facilities: issues and concerns identified by the international network prevention of elder abuse (INPEA)

2020· article· en· W3100760286 on OpenAlexaff
Marie Beaulieu, Julien Cadieux Genesse, Kevin St‐Martin

Bibliographic record

VenueThe Journal of Adult Protection · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsElder abuseContext (archaeology)OriginalityMedicineHuman rightsPandemicPolitical sciencePsychologyBusinessPublic relationsCoronavirus disease 2019 (COVID-19)Poison controlMedical emergencySuicide preventionLawDisease

Abstract

fetched live from OpenAlex

Purpose The COVID-19 pandemic has affected the physical, psychological, social and financial health of older persons. On this subject, the United Nations published a policy brief on the impact of COVID-19 on older persons in May 2020. In line with this, the purpose of this general review is to address three issues affecting older persons living in residential care facilities: protective measures implemented to block the virus’ entry, the types of mistreatment most frequently experienced and the necessity to promote and defend the rights of these persons. Design/methodology/approach The design of this study is based on input gathered since the end of April during meetings of the International Network for the Prevention of Elder Abuse (INPEA) and the results of a July survey of its members. Findings The survey results indicate variability in the implementation of protective measures in different countries and the significant presence of mistreatment and violation of the rights of older persons. Three major issues demand attention: ageism, systemic and managerial problems and the effects of implemented measures. All these prompt the INPEA to once again plea for the adoption of an international convention of human rights of older persons. Originality/value To our knowledge, this is the first article sharing the views of the INPEA from a global perspective in the context of COVID-19.

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)0.001
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 score0.245
Threshold uncertainty score0.620

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
GPT teacher head0.331
Teacher spread0.291 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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