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Record W2423698969 · doi:10.37119/ojs2016.v22i1.267

Culture in Schooling in the Inuvialuit Settlement Region

2016· article· en· W2423698969 on OpenAlexaffvenueabout
Paul D. Berger, Jennifer L. Johnston, Melissa Oskineegish

Bibliographic record

Venuein education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsInuvialuit Regional CorporationLakehead University
Fundersnot available
KeywordsSettlement (finance)SociologySocioeconomic statusEmbodied cognitionGeographyPopulationDemography

Abstract

fetched live from OpenAlex

We describe research on Inuvialuit culture in schooling in the Inuvialuit Settlement Region in the northwestern Northwest Territories in Arctic Canada. A mixed-methods case study using questionnaires in the region’s six communities explored students’, parents,’ and high school teachers’ perspectives on Inuvialuit culture in the schools. While students and parents were pleased that local culture is reflected in the schools, most would like to see more Inuvialuit culture become part of schooling. Teachers would like to know more about Inuvialuit culture and history and would like professional development to help them teach Inuvialuit students more effectively. This research suggests that policy in the Northwest Territories to move towards culturally responsive schooling is yet to be fully embodied. It should be prioritized.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.256

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.013
Scholarly communication0.0050.001
Open science0.0010.005
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 head0.019
GPT teacher head0.340
Teacher spread0.321 · 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

Citations5
Published2016
Admission routes3
Has abstractyes

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