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Record W3196389464 · doi:10.5334/ijic.icic20170

Community-driven network building in health care: creating an exploratory social space to pursue co-production following reforms

2021· article· en· W3196389464 on OpenAlexaffabout
Susan Usher

Bibliographic record

VenueInternational Journal of Integrated Care · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsPublic relationsSociologySocial network analysisLegitimacyEquity (law)Health careCommunity cohesionSustainabilityBusinessPolitical scienceEconomic growthSocial capitalEconomicsSocial science

Abstract

fetched live from OpenAlex

Community-driven network building in health care: creating an exploratory social space to pursue co-production following reformsIntroduction:Integrated care requires engaging and empowering people and communities to take an active role in designing and delivering health services (WHO 2019). Their capacities to co-produce health outcomes alongside formal providers are key to assuring sustainability and equity. However collaborative dynamics are compromised by power differentials that limit recognition of community capacities, and are vulnerable to system reforms. Much of the literature on co-production focuses on provider-side initiatives to engage communities. This paper provides an alternate view, exploring how community actors forge network alliances to gain legitimacy and power to co-produce care.Methods:We conducted a longitudinal case study of the network development efforts of a community working group (WG) concerned with access to health services following reforms in Québec, Canada. The WG brought together concerned citizens along with community organizations working with seniors, minorities, immigrants, youth, and people with disabilities. Data were collected over three years from observation, documents and interviews, and social network analysis was conducted to reveal the evolution of relationships among community actors, and between community and public actors. Actor-network theory (Callon) was used to distinguish stages of network maturation. These analyses explored how interactions contributed to identifying and opening pathways for co-production.Results:The WG pursued network building in two stages. A first focused on problem definition: WG members brought their existing networks together to validate access problems perceived in their constituencies, then reached out as a group to public sector contacts to achieve a better understanding of precisely what had changed in the system. In a second stage, the WG mobilized this network of community and public actors to equip a broader public to more effectively draw upon public and community resources to meet their needs. Two factors appeared to impede co-production: the limited influence of front-line actors on public system processes; and discrepancies between community priorities and system mechanisms for participation.Discussion:In the context of reforms, 'problematization' was an especially important stage in network development and showed signs of consensus development on 1. the existence and nature of problems, and 2. interdependencies between public and community actors in identifying and implementing solutions.Conclusions:Network development through the WG enabled community actors to gain the "organizational infrastructure" to participate in collaborative governance (Ansell and Gash 2008). Community efforts can open new spaces to enhance co-productive capacities of people and communities; public provider ability to integrate these capacities into processes is reduced by reforms.Lessons:Network interactions enable the recognition of interdependencies and the development of consensus, and in this way create conditions for collaboration even among actors of different strengths (Benson).The fragility and disruption through reforms of links between public and community actors impede co-production.LimitationsLonger follow-up and comparison with other community initiatives may have provided additional insight into community strategies for gaining legitimacy in co-production.Future researchResearch on factors limiting the effectiveness of longstanding 'concertation' venues after reforms would be helpful, as would exploration of territorial dimensions of co-production between public and community actors in healthcare services.

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)0.024
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.980
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0200.028
Scholarly communication0.0120.011
Open science0.0040.023
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.133
GPT teacher head0.460
Teacher spread0.327 · 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.

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

Citations0
Published2021
Admission routes2
Has abstractyes

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