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Record W3196330493 · doi:10.1186/s13104-021-05753-y

More than a meeting: identifying the needs of the community-based seniors’ services sector as providers of health promotion services

2021· article· en· W3196330493 on OpenAlexafffundabout
Catherine E. Tong, Joanie Sims‐Gould, Sarah Lusina‐Furst, Heather McKay

Bibliographic record

VenueBMC Research Notes · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of WaterlooUniversity of British ColumbiaVancouver Coastal Health
FundersInstitute of AgingCentre for Hip Health and MobilityMinistry of Health, British ColumbiaCanadian Institutes of Health ResearchUniversity of British ColumbiaMichael Smith Health Research BC
KeywordsSummitContext (archaeology)Promotion (chess)MedicineHealth promotionPublic relationsNursingService providerService (business)Political scienceBusinessPublic healthGeography

Abstract

fetched live from OpenAlex

OBJECTIVE: Many economically developed countries have seen a decline in publicly funded community programming. Within this context, community-based seniors' service (CBSS) organizations have been increasingly tasked to deliver programs to support the health and wellbeing of older citizens (e.g., home support, physical activity programs, and chronic disease management education). The primary objective of this study was to capture of the current needs of CBSS leaders in British Columbia, Canada, who attended a seminal event in the CBSS sector's development-the inaugural Summit on Aging. RESULTS: Our evaluation of the Summit included: pre/post Summit surveys (N = 79/76), ethnographic observations, and follow-up interviews (n = 22). Our detailed evaluation plan may inform others undertaking similar data collection; the most informative results were derived from the follow-up interviews and our findings suggest that interviews may be sufficient for similar evaluations. Summit delegates identified key opportunities to strengthen the CBSS as a sector, including enhanced collaboration; improved mechanisms that foster connecting and collaborating; and more resources, including training and qualified staff, to increase their capacity to deliver community-based health services. These findings echo work already completed in the community-based health promotion sector.

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)0.011
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.266
GPT teacher head0.477
Teacher spread0.211 · 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.

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
Published2021
Admission routes3
Has abstractyes

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