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Record W4413838789 · doi:10.24908/iqurcp19858

Re-Visioning Community Mobilization Training: Centering Indigenous Knowledge, Culture, and Self-Determination

2025· article· en· W4413838789 on OpenAlexaffvenueabout
Cameron Hare, Lucie Lévesque

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsQueen's University
Fundersnot available
KeywordsMobilizationIndigenousTraining (meteorology)Community mobilizationSociologyPolitical sciencePsychologyGeography

Abstract

fetched live from OpenAlex

Community mobilization is a self-determined process where communities draw on their culture, strengths, and resources to advance shared priorities for wellness. The Kahnawà:ke Schools Diabetes Prevention Program (KSDPP) is a long-standing example, recognized for its success in community health promotion. The Community Mobilization Training (CMT) was developed from the KSDPP model to share best practices for mobilization with communities across Turtle Island. The original CMT integrated Indigenous values and culture with Western planning models, including the PRECEDE–PROCEED framework, the Ottawa Charter for Health Promotion, and Social Cognitive Theory. While these models offer useful constructs, over time, both communities and research team members have recognized that privileging these Western frameworks within the CMT overshadowed Indigenous values that were implicitly present and essential. The time has come to strengthen the community-based foundations of the training and shift away from these models, leading instead with Indigenous culture, values, epistemologies, and practices, placing community self-determination at its core. In response, we are revitalizing the CMT to be explicitly grounded in Indigenous knowledge systems, while retaining Western program planning, implementation, and evaluation concepts where they align with Indigenous approaches and are valued by communities. Guided by Indigenous knowledge translation frameworks (e.g., Smylie et al.), our approach emphasizes respect, relationship, and reciprocity, ensuring that the CMT remains culturally resonant and supportive of community-led health promotion. Our re-visioning is informed by multiple data sources: talking circles on cultural grounding; surveys assessing community readiness; and interviews with researchers, participants and facilitators. Using a realist evaluation approach, we are developing a program theory to describe how mobilization unfolds when driven by Indigenous ways of knowing and doing. By rooting the training in Indigenous strengths and knowledges, the revised CMT better captures the realities of communities and the central role of culture in driving collective wellness across Turtle Island.

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)0.033
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0130.027
Scholarly communication0.0110.013
Open science0.0030.023
Research integrity0.0030.013
Insufficient payload (model declined to judge)0.0050.001

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 head0.164
GPT teacher head0.440
Teacher spread0.275 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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".

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Citations0
Published2025
Admission routes3
Has abstractyes

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