MétaCan
Menu
Back to cohort
Record W2586592628 · doi:10.1111/1467-9566.12453

Relational citizenship: supporting embodied selfhood and relationality in dementia care

2017· article· en· W2586592628 on OpenAlexafffund
Pia Kontos, Karen‐Lee Miller, Alexis P. Kontos

Bibliographic record

VenueSociology of Health & Illness · 2017
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsPublic Health OntarioToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsEmbodied cognitionCitizenshipDementiaSociologyPsychologyAestheticsEpistemologyPolitical scienceMedicinePhilosophyPoliticsDiseaseLaw

Abstract

fetched live from OpenAlex

We draw on findings from a mixed-method study of specialised red-nosed elder-clowns in a long-term care facility to advance a model of 'relational citizenship' for individuals with dementia. Relational citizenship foregrounds the reciprocal nature of engagement and the centrality of capacities, senses, and experiences of bodies to the exercise of human agency and interconnectedness. We critically examine elder-clown strategies and techniques to illustrate how relational citizenship can be supported and undermined at the micro level of direct care through a focus on embodied expressions of creativity and sexuality. We identify links between aesthetic enrichment and relational practices in art, music and imagination. Relational citizenship offers an important rethinking of notions of selfhood, entitlement, and reciprocity that are central to a sociology of dementia, and it also provides new ethical grounds to explore how residents' creative and sexual expression can be cultivated in the context of long-term care.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.019
Scholarly communication0.0080.005
Open science0.0020.015
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.240
GPT teacher head0.465
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations161
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueSociology of Health & IllnessSame topicMental Health and Patient InvolvementFrench-language works237,207