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Record W3202429365 · doi:10.1080/09687599.2021.1976112

Empowering younger residents living in long-term care homes as co-researchers

2021· article· en· W3202429365 on OpenAlexafffund
Katie Aubrecht, Brittany Barber, Melanie Gaunt, Joanne Larade, Vicky Levack, Marie Earl, Lori E. Weeks

Bibliographic record

VenueDisability & Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsDalhousie UniversitySt. Francis Xavier University
FundersNova Scotia Health Research Foundation
KeywordsParticipatory action researchLong-term careExperiential knowledgeAssisted livingAssisted Living FacilityIndependent livingGerontologyLived experienceExperiential learningCitizen journalismPsychologyNursingPublic relationsSociologyMedicinePedagogyPolitical science

Abstract

fetched live from OpenAlex

We draw on our research, our lived experiences of disability and the grounded expertise of disabled persons living in long-term care (LTC) homes as co-researchers, to illustrate the value of disability-led participatory research. Our approach to a co-designed collaborative project on young adults living in LTC highlights the benefits of research that centers the lived realities of disabled people. Points of interestResearch and knowledge about disabled people living in long-term care (LTC) homes routinely excludes the perspectives of the people who live there; this is especially true for younger residents living in LTC.This article shares information about a study on promising approaches to residential LTC for people under 65 years of age that was co-led with care home resident researchers.The study design provided opportunities and supports to encourage meaningful engagement, such as training and access to research assistants.Resident co-researchers brought lived expertise and experiential insights that enriched the research process and knowledge produced, and that supported them in their own disability advocacy work.Inequities persist when budgets fail to consider and address barriers to residents’ full participation in all aspects of the research.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.087
GPT teacher head0.470
Teacher spread0.383 · 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 designObservational
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

Citations13
Published2021
Admission routes2
Has abstractyes

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