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Record W3088696954 · doi:10.1007/s11266-020-00252-3

Promising Practices of Nonprofit Organizations to Respond to the Challenges Faced in Countering the Mistreatment of Older Adults

2020· article· en· W3088696954 on OpenAlexafffundabout
Marie Beaulieu, Isabelle Maillé, Jordan Bédard-Lessard, Hélène Carbonneau, Sophie Éthier, Julie Fortier, Andrée Sévigny

Bibliographic record

VenueVOLUNTAS International Journal of Voluntary and Nonprofit Organizations · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsUniversité LavalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversité du Québec à Trois-RivièresHealth and Social Services Centre University Institute of Geriatrics of SherbrookeCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanUniversité de Sherbrooke
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDocumentationNonprofit organizationPublic relationsBusinessBest practicePsychologyMedical educationNursingMedicinePolitical science

Abstract

fetched live from OpenAlex

Abstract This article discusses promising practices used by employees and volunteers in nonprofit organizations (NPOs) in countering the mistreatment of older adults (CMOA). The findings presented here are the result of research on the material and financial actions of NPOs in CMOA, based on multiple case studies in five active Canadian NPOs in the framework of CMOA. The body of data comprises organizational documentation from NPOs, socio-demographic questionnaires and group or individual interviews with 64 participants (management volunteers, employees, field volunteers and accompanied older adults). Themed intra- and intercase analyses were carried out. Some key challenges faced by the active NPOs in CMOA include the continuity of follow-ups, difficulty in reaching older adults and obstacles to requesting help. Promising practices that have been implemented to contribute to the response to these challenges, such as collaboration practices, proactive prevention activities, canvassing and shelter services, are considered.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.024
GPT teacher head0.321
Teacher spread0.297 · 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

Citations0
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueVOLUNTAS International Journal of Voluntary and Nonprofit OrganizationsSame topicElder Abuse and NeglectFrench-language works237,207