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Record W2070971120 · doi:10.1177/1471301214563551

Negotiating access to a diagnosis of dementia: Implications for policies in health and social care

2014· article· en· W2070971120 on OpenAlexaffabout
Sharon Koehn, Melissa Badger, Carole Cohen, Lynn McCleary, Neil Drummond

Bibliographic record

VenueDementia · 2014
Typearticle
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversity of AlbertaHealth Sciences CentreSunnybrook Health Science CentreBrock UniversitySimon Fraser UniversityProvidence Health Care
Fundersnot available
KeywordsDementiaNegotiationSocial careHealth carePsychologyGerontologyMedicinePolitical scienceNursingSociologyDiseaseSocial science

Abstract

fetched live from OpenAlex

The 'Pathways to Diagnosis' study captured the experience of the prediagnosis period of Alzheimer's disease and related dementias through indepth interviews with 29 persons with dementia and 34 of their family caregivers across four sites: anglophones in Calgary, francophones in Ottawa, Chinese-Canadians in Greater Vancouver and Indo-Canadians in Toronto. In this cross-site analysis, we use the 'Candidacy' framework to comprehensively explore the challenges to securing a diagnosis of dementia in Canada and to develop relevant health and social policy. Candidacy views eligibility for appropriate medical care as a process of joint negotiation between individuals and health services, which can be understood relative to seven dimensions: identification of need, navigation, appearances at services, adjudication by providers, acceptance of/resistance to offers, permeability of services and local conditions. Interviewees experienced challenges relative to each of the seven dimensions and these varied in form and emphasis across the four ethno-linguistic groups.

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)0.000
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 score0.030
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.073
GPT teacher head0.461
Teacher spread0.388 · 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

Citations23
Published2014
Admission routes2
Has abstractyes

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