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Record W2943889530 · doi:10.1080/22423982.2019.1571381

Structures last longer than intentions: creation of Ongomiizwin – Indigenous Institute of Health and Healing at the University of Manitoba

2019· article· en· W2943889530 on OpenAlexaffabout
Catherine Cook, Melanie MacKinnon, Marcia Anderson, Ian Whetter

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of ManitobaFirst Nations Health and Social Secretariat of Manitoba
Fundersnot available
KeywordsIndigenousMentorshipExcellenceMandateParticipatory action researchMedical educationCommissionCommunity engagementHealth carePolitical scienceSociologyPublic relationsMedicine

Abstract

fetched live from OpenAlex

Ongomiizwin - Indigenous Institute of Health and Healing at the University of Manitoba's Rady Faculty of Health Sciences (RFHS) was launched in June of 2017 with a mandate to provide leadership and advance excellence in research, education and health services to achieve health and wellness for Indigenous peoples and to implement the Truth and Reconciliation Commission of Canada's Calls to Action within the Faculty. The RFHS Reconciliation Action Plan has five broad themes: (1) Honoring traditional knowledge systems and practices, (2) Safe learning environments and professionalism, (3) Student support, mentorship and retention (4) Education across the spectrum and 5) Closing the gap in admissions. Community engagement is the focus of our work. Learners and practicing clinicians are grounded in the knowledge of ongoing colonial harms, engaged in critical self-reflection on one's own biases and trained to confront anti-indigenous racism in health care. This alignment is changing the health human resource landscape in northern Manitoba and beyond.

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)0.006
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.512

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.007
Scholarly communication0.0070.002
Open science0.0020.011
Research integrity0.0020.006
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 head0.017
GPT teacher head0.301
Teacher spread0.284 · 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 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

Citations14
Published2019
Admission routes2
Has abstractyes

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Same venueInternational Journal of Circumpolar HealthSame topicIndigenous Health, Education, and RightsFrench-language works237,207