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Record W4382918293 · doi:10.1080/08959420.2023.2226341

Gaps in the System: Supporting People Living with Dementia

2023· article· en· W4382918293 on OpenAlexafffund
Madeline King, Allie Peckham, Husayn Marani, Monika Roerig, Seles Yung, Kimberlyn McGrail, Yuchi Young, James Shaw, Gregory P. Marchildon

Bibliographic record

VenueJournal of Aging & Social Policy · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
FundersCanadian Institutes of Health ResearchAlzheimer Society
KeywordsDementiaAssisted livingGerontologyIndependent livingPsychologyActivities of daily livingNursingMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Persons living with dementia and their caregivers often face challenges in accessing support for their complex needs. This study aims to understand how program administrators, people living with dementia, unpaid caregivers, and decision-makers perceive specific dementia care programs and whether they are adequately meeting the needs of individuals living with dementia. Forty semi-structured interviews were conducted between 2018 and 2020 in five North American jurisdictions. Three main gaps were identified (1) disconnected system infrastructure, (2) lack of comprehensive services to meet diverse needs, and (3) inconsistent understandings of dementia. Despite having programs in place, there remain significant limitations in systems that could be addressed to adequately meet the needs of individuals living with dementia and their caregivers.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.005
Scholarly communication0.0040.006
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.358
Teacher spread0.339 · 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 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

Citations15
Published2023
Admission routes2
Has abstractyes

Explore more

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