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Implications of Discourse: A Trilogy of Educational Policy

2012· article· en· W330786795 on OpenAlexafffundvenueabout
Lorenzo Cherubini

Bibliographic record

VenueAlberta Journal of Educational Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of CanadaMinistère de l’Éducation, Gouvernement de l’Ontario
KeywordsTrilogyEducational researchPsychologySociologyDiscourse analysisPedagogyLinguisticsHistory

Abstract

fetched live from OpenAlex

The learning ministries in Ontario have made a concerted effort to underscore Aboriginal learners' needs and preferences in publicly-funded and assisted schools and training services throughout the province.Through a trilogy of policy documents, the Ontario Ministry of Education (OME) and the Ministry of Training, Colleges and Universities (MTCU) have addressed expanded definitions of learning and sought to unfold the socio-cultural and epistemic values related to Aboriginal student and community worldviews:1.The Ontario First Nation, Métis and Inuit Education Policy Framework (2007) commissions the province's boards of education, school administrators and teachers to create culturally-sensitive schools and classrooms.2. The OME's Sound Foundations for the Road Ahead (2009) is a progress report on the outcomes for the aforementioned Policy Framework (2007) and aims to assure taxpayers that progress is being made in regards to policy implementation.

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)0.046
metaresearch head score (Gemma)0.089
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.907
Threshold uncertainty score0.396

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.089
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0090.010
Science and technology studies0.0390.115
Scholarly communication0.0430.040
Open science0.0060.018
Research integrity0.0220.022
Insufficient payload (model declined to judge)0.0120.001

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 head0.177
GPT teacher head0.574
Teacher spread0.397 · 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

Citations3
Published2012
Admission routes4
Has abstractyes

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