MétaCan
Menu
Back to cohort
Record W3001385095 · doi:10.1017/s0714980819000540

Older Adults’ Views on the Repositioning of Primary and Community Care

2020· article· en· W3001385095 on OpenAlexaff
Wendy Hulko, Noeman Mirza, Lori Seeley

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsInterior HealthThompson Rivers University
Fundersnot available
KeywordsRestructuringPrimary careGerontologyOptimismMedicineService (business)IndigenousFamily medicineNursingPsychologyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Older adults are rarely consulted on health care restructuring. To address this gap, our study explored older adults' views on "repositioning", a restructuring initiative to support independent living for older adults with complex chronic disease (CCD). We collected and analysed data from 83 older adults living in one small city and nine rural small towns where "repositioning" of primary and community care was occurring. Average participant age was 75 years; 56 (67%) were women, 44 (53%) had CCD, and 20 (24%) identified as Indigenous or South Asian. The four themes were: unfamiliarity with repositioning; optimism versus skepticism; improving primary and community care (through better home care, improved transportation, and more doctors); and, playing an active role to effect change. For repositioning to be successful, diverse service users must be fully included; rural-dwelling older adults' priorities for primary and community care need to be addressed, rather than using a "cookie-cutter" approach.

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)0.007
metaresearch head score (Gemma)0.016
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 score0.954
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
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 head0.028
GPT teacher head0.257
Teacher spread0.229 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicHealth disparities and outcomesFrench-language works237,207