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Record W2562602535

The Governance of Developmental Disability Supports for Older Adults in Ontario and Québec

2016· dissertation· en· W2562602535 on OpenAlexaboutno aff
Daniel Dickson

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2016
Typedissertation
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyCorporate governanceQuality of life (healthcare)PopulationLife expectancyInclusion (mineral)PsychologyPolitical scienceGerontologySociologyMedicineNursingBusinessSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT
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\nThe Governance of Developmental Disability Supports for Older Adults in Ontario and Québec
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\nDaniel Dickson
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\nThis project aims to analyze the effects of Canadian provincial governance structures on support work provision for older adults with developmental disabilities. Drawing from multilevel governance literature, it compares Ontario's more centralized and policy-driven governance structure with Québec's more disentangled and multi-jurisdictional structure, which gives more autonomy to developmental support agencies in planning support provision. To facilitate this comparison the project uses semi-structured interviews with personal support workers for older adults with developmental disabilities in both provinces. By using an 'institutional ethnography' interview methodology, the work experiences of primary support workers are situated within operant policies and rules, specifically with respect to supporting their clients in 'social inclusion', a widely recognized core domain for quality of life outcomes for adults with developmental disabilities. Owing to dramatic improvements in life expectancy resulting from healthcare advancements and deinstitutionalization, Canadians with developmental disability are increasingly living into older age. Consequently, support work practice is challenged by the intersection of social constructions of aged and disabled identities, which can act against the social inclusion of this ‘new’ population. By comparing these two divergent provincial governance structures from the important perspectives of frontline workers, this project contributes to a discussion of best practices in Canadian policy and administration.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.996

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 studies0.0010.001
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 head0.032
GPT teacher head0.320
Teacher spread0.288 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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