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Record W2197614560 · doi:10.55016/ojs/ajer.v61i1.56031

(Non)Construction of the Teacher: An Inquiry into Ontario’s Equity and Inclusive Education Strategy

2015· article· en· W2197614560 on OpenAlexaffvenueabout
Kevin Naimi, Jeanette Cepin

Bibliographic record

VenueAlberta Journal of Educational Research · 2015
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEquity (law)Context (archaeology)Educational equityPublic policyTeacher educationPedagogyEducation policyPolitical sciencePolicy analysisStudent achievementPublic relationsPsychologySociologyMathematics educationAcademic achievementPublic administrationHigher education

Abstract

fetched live from OpenAlex

In this paper we perform a critical discourse analysis on the policy document Ontario’s Equity and Inclusive Education Strategy (2009). We examine the three core priorities the policy outlines: improve student achievement, reduce achievement gap and increase public confidence in public education. This document is approached from the context of new managerial educational reforms, to understand how the teacher is positioned within this policy. This policy, while laudable in intention, excludes the voice of the teacher. The policy offers much in the way of enhancing the students’ experience yet says little about the role of the classroom teacher or how the policy might be translated and facilitated into schools/classrooms across the province.

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)0.014
metaresearch head score (Gemma)0.017
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 score0.207
Threshold uncertainty score0.920

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.017
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0300.043
Scholarly communication0.0110.005
Open science0.0020.005
Research integrity0.0040.004
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 head0.481
GPT teacher head0.627
Teacher spread0.146 · 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

Citations7
Published2015
Admission routes3
Has abstractyes

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