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Record W2966788671 · doi:10.1177/1177180119866515

“I would prefer to have my health care provided over a cup of tea any day”: recommendations by urban Métis women to improve access to health and social services in Toronto for the Métis community

2019· article· en· W2966788671 on OpenAlexafffundabout
Renée Monchalin, Janet Smylie, Cheryllee Bourgeois, Michelle Firestone

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsToronto Metropolitan UniversitySt. Michael's HospitalUniversity of VictoriaPublic Health OntarioUniversity of Toronto
FundersInstitute of Aboriginal Peoples Health
KeywordsIndigenousDeskSocial workCommunity healthMetisSociologyService providerPublic relationsNursingMedicineService (business)Medical educationPublic healthPolitical scienceBusinessMarketing

Abstract

fetched live from OpenAlex

This article reports on recommendations made by urban Métis women for improving access to health and social services in Toronto, Canada. By applying a conversational method, this research followed up with a subgroup of urban Métis women who participated in the Our Health Counts Toronto longitudinal cohort. Métis women ( n = 11) provided holistic and practical recommendations for improving access to health and social services. These recommendations include (a) Métis presence, (b) holistic interior design, (c) Métis specific or informed service space, (d) welcoming reception/front desk, and (e) culturally informed service providers. During the conversations, the women shared positive experiences with an Indigenous-informed midwifery practice called Seventh Generation Midwives Toronto. Examples from the women will be provided of Seventh Generation Midwives Toronto to illustrate how the recommendations may look in practice. This research illustrates that Métis women hold solutions for improving access to health and social services for the Métis community.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.389
Teacher spread0.365 · 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.

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

Citations16
Published2019
Admission routes3
Has abstractyes

Explore more

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