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Record W4386324980 · doi:10.18584/iipj.2023.14.2.14072

Does Participation in Full-Time Kindergarten Improve Metis Students’ School Outcomes? A Longitudinal Population-Based Study from Manitoba, Canada

2023· article· en· W4386324980 on OpenAlexaffvenueabout
Emily Brownell, Jennifer Enns, Julianne Sanguins, Marni Brownell, Mariette Chartier, Dan Château, Joykrishna Sarkar, Elaine Burland, Aynslie Hinds, Alan Katz, Rob Santos, A. Frances Chartrand, Nathan Nickel

Bibliographic record

VenueInternational Indigenous Policy Journal · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of ManitobaManitoba Health
Fundersnot available
KeywordsMetisPopulationAcademic yearGeneral partnershipIndigenousPsychologyMedical educationSociologyDemographyPolitical scienceMathematics educationMedicineBiologyEcologyComputer science

Abstract

fetched live from OpenAlex

This study, a partnership between and , investigated whether attending full-time kindergarten (FTK) was associated with better educational outcomes for Metis students in Manitoba, who may face unique barriers to academic success. We utilized linked administrative data from the Manitoba Population Research Data Repository. For each measured education outcome, there were no significant differences in how Metis students who attended FTK vs Metis students who attended half-time kindergarten (HTK) performed. FTK does not provide sufficient support to Metis students to overcome the structural barriers to academic success they may face. It is likely that an upstream approach to addressing the structural barriers is needed to support improved outcomes in this population.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.004
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.364
Teacher spread0.341 · 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 designObservational
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
Published2023
Admission routes3
Has abstractyes

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Same venueInternational Indigenous Policy JournalSame topicEarly Childhood Education and DevelopmentFrench-language works237,207