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Record W2296296821 · doi:10.7202/1036109ar

Neo-colonialism in Our Schools: Representations of Indigenous Perspectives in Ontario Science Curricula

2016· article· en· W2296296821 on OpenAlexaffvenueabout
Eun-Ji Amy Kim

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsMcGill University
Fundersnot available
KeywordsCurriculumIndigenousChristian ministryColonialismRepresentation (politics)PedagogyContent analysisSociologyIndigenous educationState (computer science)Political scienceSocial scienceLawPoliticsEcology

Abstract

fetched live from OpenAlex

Motivated by the striking under-representation of Indigenous students in the field of science and technology, the Ontario Ministry of Education has attempted to integrate Aboriginal perspectives into their official curricula in hopes of making a more culturally relevant curriculum for Indigenous students. Using hermeneutic content analysis (HCA), a mixed-method framework for analyzing content, this study examined how and to what extent Aboriginal content is represented in Ontario’s official science curriculum documents. Given that very little has been published in this specific area, this research sheds light on the current state of the representation of Aboriginal cultures in contemporary Canadian science curriculum.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.063
Threshold uncertainty score0.460

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0190.017
Scholarly communication0.0060.002
Open science0.0010.007
Research integrity0.0010.002
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 head0.225
GPT teacher head0.445
Teacher spread0.220 · 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

Citations27
Published2016
Admission routes3
Has abstractyes

Explore more

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