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Record W2495760496 · doi:10.1007/978-94-6209-593-9

How Black and Working Class Children Are Deprived of Basic Education in Canada

2014· book· en· W2495760496 on OpenAlexaboutno aff
Bairu Sium

Bibliographic record

VenueSensePublishers eBooks · 2014
Typebook
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Working classMathematics educationPsychologySociologyPolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This book is the culmination of twenty-four years of research. It explores the thematic intersections of race, class, immigration, and the potential of building student-centered classrooms. Of course, the building of a truly student-centered is itself a slow and contested process. Over the years, progressive changes towards more inclusive education made by some governments were dismantled by others, and have left disadvantaged children where they were before the study was launched. In the meantime, the system has perfected the process of streaming minority children to dead-end courses that betray the social and economic mobility advertised to them. This book examines the moments and positions of educational betrayal in which racialized and working class students disproportionately find themselves. For many, at that point the only option is to drop out of school and engage in the drug trade or other lifestyles that put them at further risk. This is a longitudinal study of a kind with respect to reform and changes retained in education. It started with eight months observation of a split level grade five and six classroom in September 1986. That was instrumental in identifying the uphill battle that black, working class and new immigrant children and their parents were facing to secure the education they deserved. Through continued reviews, observation and follow up interviews change or lack of it was traced. The results call for urgent overhaul of the way education is provided to all children. The book ends with suggestions to effect change.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.318
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.249
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2014
Admission routes1
Has abstractyes

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