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Record W2940220875

A critical discourse analysis of Manitoba’s safe schools documentation and implications for students

2018· article· en· W2940220875 on OpenAlexaboutno aff
Cara Colorado

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsDocumentationCritical discourse analysisSociologyPublic relationsPedagogyPsychologyMedical educationLinguisticsMathematics educationPolitical scienceMedicineComputer scienceLawPoliticsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Students who have been labeled as exhibiting behaviour difficulties in the school system have some of the worst academic and social outcomes of any student group. In most Canadian provinces, responses to student behaviour and misbehavior are legislated through Safe Schools policies, directives, guidelines and curriculum support documents, which guide school districts and individual schools in responding to student behaviour and misbehavior. This project aims to conduct a critical discourse analysis of Manitoba’s Safe and Caring Schools documentation in order to consider the ways in which provincial policy directives and guidelines construct children and their behaviours and subsequently to consider how to better support students, particularly those who tend to be marginalized by existing school based responses to student behaviour. By deconstructing the ways in which children, behaviours, and school responses are constructed in policy documents, the project aims to make recommendations for policy-makers and educators to better support students, particularly those who are most marginalized by/within the school system.

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)0.015
metaresearch head score (Gemma)0.015
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 score0.249
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.008
Science and technology studies0.0410.028
Scholarly communication0.0130.003
Open science0.0020.006
Research integrity0.0020.005
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 head0.049
GPT teacher head0.408
Teacher spread0.359 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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