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Record W4398137441 · doi:10.1017/s0714980824000217

Consent and Inclusion of People Living with Dementia (PLWD) in Research: Establishing a Canadian Agenda for Inclusive Rights-Based Practices

2024· article· en· W4398137441 on OpenAlexafffundabout
Amanda Grenier, Deborah O’Connor, Krista James, Daphne Imahori, Daniella Minchopoulos, Nicole Velev, Laura Tamblyn-Watts, Jim Mann

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2024
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsUniversity of British ColumbiaBaycrest HospitalUniversity of Toronto
FundersAlzheimer Society
KeywordsInclusion (mineral)PersonhoodLegislationDementiaPublic relationsSociologyPolitical scienceHappeningConceptual frameworkPublic administrationLawMedicineSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: People living with dementia (PLWD) may want to participate in research, but the guidelines and processes enacted across various contexts may prohibit this from happening. OBJECTIVE: Understanding the experiences of people with lived experiences of dementia requires meaningful inclusion in research, as is consistent with rights-based perspectives. Currently, the inclusion of PLWD in Canadian research is complex, and guidelines and conceptual frameworks have not been fully developed. METHODS: This research note outlines a three-year proof-of-concept grant on the inclusion and consent of PLWD in research. FINDINGS: It presents a brief report on some of the contradictions and challenges that exist in legislation, research guidelines, and research practices and raises a series of questions as part of an agenda on rights and inclusion of PLWD in research. DISCUSSION: It suggests conceptual, legal, and policy issues that need to be addressed and invites Canadian researchers to re-envision research practices and to advocate for law and policy reform that enables dementia research to align and respect the rights and personhood of PLWD.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.838
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.074
GPT teacher head0.384
Teacher spread0.310 · 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.

Study designNot applicable
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

Citations7
Published2024
Admission routes3
Has abstractyes

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