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Record W4226454766 · doi:10.18584/iipj.2021.12.4.13690

Understanding Manitoba Inuit’s Social Programs Utilization and Needs: Methodological Innovations

2022· article· en· W4226454766 on OpenAlexaffvenueabout
Josée G. Lavoie, Leah McDonnell, Nathan Nickel, Wayne Clark, Caroline Anawak, Jack Anawak, Levinia Brown, Grace Clark, Maata Evaluardjuk-Palmer, Frederick Ford, Rachel Dutton, Alan Katz, Sabrina T. Wong

Bibliographic record

VenueInternational Indigenous Policy Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of AlbertaUniversity of British ColumbiaMakivik CorporationManitoba HealthUniversity of Manitoba
Fundersnot available
KeywordsGeneral partnershipSocial WelfareIndigenousWelfareGeographyEconomic growthSocioeconomicsPolitical scienceGerontologyLibrary scienceSociologyMedicineEcology

Abstract

fetched live from OpenAlex

Manitoba is home to approximately 1,500 Inuit, and sees 16,000 consults yearly from the Kivalliq region of Nunavut to access services. The purpose of our study was to develop detailed profiles of Inuit accessing services in Manitoba, by using administrative data routinely collected by Manitoban agencies, to support the development of Inuit-centric services. This study was conducted in partnership with the Manitoba Inuit Association, and Inuit Elders from Nunavut and Manitoba. Findings shows that the Inuit community living in Manitoba is fairly stable, with only approximately 5 percent of Inuit moving in and out of Manitoba on any given year. Inuit settle primarily in Winnipeg, and a significant proportion depend on social programs such as Income Assistance and housing support. A significant number of Inuit children have contact with the Child Welfare System. Our results support the need for more Inuit-centric programming, including family support and language programs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
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
Bibliometrics0.0010.001
Science and technology studies0.0270.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.415
GPT teacher head0.449
Teacher spread0.034 · 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 designNot applicable
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

Citations5
Published2022
Admission routes3
Has abstractyes

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