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Record W7001016984

How to teach bad boys a lesson: Student experiences of behaviour support in mainstream schools and secondary alternate education programs

2022· dissertation· en· W7001016984 on OpenAlexaboutno aff

Bibliographic record

VenueSummit (Simon Fraser University) · 2022
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation Discipline and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsMainstreamFeelingQualitative researchEconomic JusticeDisciplineSemi-structured interviewSchool disciplinePoint (geometry)
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study examines the experiences of Canadian secondary school students who are enrolled in Behaviour Support-focused alternate school programs. Through semi structured interviews, I investigate students’ understandings of their experiences as alternate school students and students who transitioned from mainstream to alternate schools. Three themes emerged in the data including ordinary violence in lives of the students, consistently disrupted education, tenuous feelings of belonging at school, and desire for connection. My findings suggest that traditional approaches of behaviour support do not address systemic inequalities and individualize ‘problem’ students to the point of harm. The findings suggest that behaviour-support programs have the potential to improve students’ education by abandoning exclusionary disciplinary practices and working to integrate equity-focused approaches such as Restorative Justice in Education, Culturally Sustaining Pedagogy, and Anti-racist education. Finally, implications for schools, pedagogical approaches, and behaviour support policies are discussed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.324
Teacher spread0.303 · 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 teacher head, not a consensus.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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