MétaCan
Menu
Back to cohort
Record W2788817076 · doi:10.1177/1049732318756056

Innovating for Transformation in First Nations Health Using Community-Based Participatory Research

2018· article· en· W2788817076 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueQualitative Health Research · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversity of ManitobaFirst Nations Health and Social Secretariat of Manitoba
FundersInstitute of Aboriginal Peoples HealthSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungResearch Manitoba
KeywordsBlueprintConceptualizationCommunity-based participatory researchParticipatory action researchCitizen journalismPublic relationsQualitative researchSociologyHealth careCommunity healthVariety (cybernetics)Knowledge managementPolitical scienceSocial scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Community-based participatory research (CBPR) provides the opportunity to engage communities for sustainable change. We share a journey to transformation in our work with eight Manitoba First Nations seeking to improve the health of their communities and discuss lessons learned. The study used community-based participatory research approach for the conceptualization of the study, data collection, analysis, and knowledge translation. It was accomplished through a variety of methods, including qualitative interviews, administrative health data analyses, surveys, and case studies. Research relationships built on strong ethics and protocols to enhance mutual commitment to support community-driven transformation. Collaborative and respectful relationships are platforms for defining and strengthening community health care priorities. We further discuss how partnerships were forged to own and sustain innovations. This article contributes a blueprint for respectful CBPR. The outcome is a community-owned, widely recognized process that is sustainable while fulfilling researcher and funding obligations.

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.

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)0.297
metaresearch head score (Gemma)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.2970.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0260.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
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 head0.992
GPT teacher head0.876
Teacher spread0.116 · 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