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Record W4400889629 · doi:10.5334/ijic.8149

The Third Sector in Integrated Care: Partner, Provider, or Both?

2024· article· en· W4400889629 on OpenAlexaffabout
Michelle Nelson, Marianne Saragosa, Robin Miller

Bibliographic record

VenueInternational Journal of Integrated Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsLunenfeld-Tanenbaum Research Institute
Fundersnot available
KeywordsIntegrated careBusinessNursingHealth careMedicinePolitical science

Abstract

fetched live from OpenAlex

Third-sector organizations (TSOs) are recognized for having a unique and essential role in designing and delivering community-centred, sustainable health and well-being services. A World Café workshop at the 2023 International Conference on Integrated Care to explore perspectives on the questions explored the question: How do we characterize the role of the Third Sector in Integrated Care Systems? Are they Partners, Service Providers, Both or Neither? Attendees from Canada, England, Scotland, Wales, Ireland, Belgium, Denmark, and the Netherlands shared perspectives regarding facilitators and barriers to engaging TSOs in integrated care systems, drawing on experiences and practices from their communities and health systems. Building from participant perspectives, we posit that while cross-sectoral alliances between government and voluntary organizations are possible, and this engagement can contribute substantial health-promoting value to society, much work remains to be done. Meaningful collaboration requires attitudinal shifts, new working methods, rebalancing power within the relationships, and sufficient resources to support the collaboration. Creative approaches to facilitating positive engagement of TSOs within integrated care systems can address long-standing barriers and misunderstandings. Sharing and learning through research, evaluations, and networks is essential to achieve integrated care systems based on trust and committed collaboration.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.034
GPT teacher head0.393
Teacher spread0.359 · 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 designNot applicable
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

Citations6
Published2024
Admission routes2
Has abstractyes

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