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Record W4413358648 · doi:10.5334/ijic.nacic24247

Strengthening multi-sector community driven team-based approaches to develop and implement sustainable supports

2025· article· en· W4413358648 on OpenAlexaboutno aff
Shannon Freeman, H. Douglas Lightfoot, Emma Rossnagel, Richard McAloney

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
Fundersnot available
KeywordsProcess managementBusinessKnowledge managementEngineering managementPublic relationsComputer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

Background: In rural communities in Canada, community-driven initiatives commonly emerge to fill the gaps in health outcomes, lack of resources, and fragmentation of available supports. These community-based solutions, often rely on a limited number of community champions and localized organizations. These organically tailored community- specific initiatives address the needs of the community of focus with consideration of the unique environmental context and often with finite human and financial resources available. There is much that academic and health systems leaders can do to support these community champions and localized organizations in the implementation and sustainability of programs, especially for the growing number of persons who are living with dementia in rural communities. We will present two case studies from two provinces which highlight the value and process to support community identified priorities to make impactful change. We then will challenge participants to consider how they can apply the strategies and resources to their own contexts as well as to identify potential challenges and mitigation strategies they may encounter. This workshop is tailored for any academic or health care professional interested in better supporting community driven initiatives. Approach: Introduction and Land Acknowledgement(7minutes) We will set the stage for aging in rural and northern communities in Canada and describe the growing needs of persons living with dementia. We will introduce the value of a community partnered approach to implementation in the context of enhancing individual and community wellbeing.Case Study -(9minutes) This Connecting People Community for Living Well initiative is a partnership between 5 community teams and the grant-funded team working to improve the wellbeing of those affected by dementia and the collaborative itself through multisector collaboration. This is achieved through the implementation of the 5 components of the Connecting People Community for Living Well model - Provincial support, Communities advancing local work, 0 guiding principles of the model, The Wellbeing Guide, and the Competency Framework. The community teams membership includes those with lived experience, service providers, service organizations, businesses, and local residents.This case study will showcase how data was gathered in partnership with the community teams through regular touch bases, focus groups, and completion of the Wellbeing guide. This information guided the development of a Lessons Learned document, infographics, competency framework, as well as the overall initiative evaluation report, including Social Return on Investment. Case Study 2-(9minutes) The Centre for Technology Adoption for Aging in the North(CTAAN), a national innovation hub built on a partnership between UNBC, Northern Health, and AGE-WELL, supports older adults to live well in by bridging the gap to make technologies more accessible. CTAAN focuses on testing, piloting, implementing, and promoting new and existing technology solutions tailored to support older adults and caregivers in northern and rural communities.This case study will showcase how CTAAN co-develops projects and establish partnerships to meet needs of our northern and rural stakeholders. We will provide an overview on our strategies to understand the individual or community specific challenges and needs, as well as the operations of the many stakeholders in our communities. We will then share how we co-develop projects with the fundamental principle of the inclusion of all stakeholders.Workshop Activity(35minutes)-Attendees will be put in small groups and be provided the wellbeing guide to review and reflect on. Each group will brainstorm potential barriers/challenges and then match these to potential mitigation strategies/resources needed to address them.(20minutes) Next, each group will share back examples to the larger groups. We will also allow opportunity for large group discussion, comments, and questions.(0minutes)We will have 5 minutes for concluding remarks.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.585

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 integrity0.0000.001
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 head0.048
GPT teacher head0.280
Teacher spread0.232 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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