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Record W4407601756 · doi:10.1177/11771801251319274

Understanding the circle of care: Indigenous service providers’ perspectives on health and well-being

2025· article· en· W4407601756 on OpenAlexaffabout
Jenna Quelch, Muna Aden, Elaine Toombs, Chris Sanders, Candida Sinoway, Christopher J. Mushquash, Linda Barkman, Melissa Deschamps, Sherri Pooyak, Meghan Young, Holly Gauvin, Anita C. Benoit

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsWomen's College HospitalHIV Legal NetworkAIDS VancouverLakehead UniversityThe Scarborough HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsIndigenousService providerNursingService (business)Health careBusinessSociologyMedicinePolitical scienceMarketing

Abstract

fetched live from OpenAlex

There is a need for broadening understandings of health and well-being to fill the critical and persistent gap in culturally safe health and social service provision for Indigenous populations. While the importance of Indigenous cultural interventions in healthcare is increasingly recognized and the perspective of Indigenous patients increasingly sought, there has been little research on the views of Indigenous service providers themselves. Our study explores the views of Indigenous service providers and how they conceptualize and deliver health and social services, including how these services link to the principles of harm reduction. We conducted one-on-one semi-structured interviews and socio-demographic questionnaires with eight Indigenous emergency service providers from Thunder Bay, Ontario, in the Fall of 2021. The results reveal broad conceptions of health and well-being with a particular focus on harm reduction principles in delivering a wide range of services that address physical, mental, and spiritual health needs.

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)0.009
metaresearch head score (Gemma)0.011
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 score0.355
Threshold uncertainty score0.706

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.026
Scholarly communication0.0060.005
Open science0.0010.007
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.340
Teacher spread0.313 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueAlterNative An International Journal of Indigenous PeoplesSame topicIndigenous Health, Education, and RightsFrench-language works237,207