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Record W3169441681 · doi:10.7202/1078519ar

Class Size and Teacher Work: Research Provided to the BCTF in their Struggle to Negotiate Teacher Working Conditions

2021· article· en· W3169441681 on OpenAlexaffvenueabout
Dan Laitsch, Hien Nguyen, Christine Ho Younghusband

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsUniversity of Northern British ColumbiaSimon Fraser University
FundersUniversity of RochesterAmerican Educational Research Association
KeywordsSupreme courtGraduation (instrument)Class sizeNegotiationClass (philosophy)PsychologyPolitical scienceMathematics educationSociologyLawMathematicsComputer science

Abstract

fetched live from OpenAlex

This paper presents an update of a 2010-literature review on class size research completed as background in preparation of an affidavit on class size provided by the lead author in the case of British Columbia Teachers’ Federation v. British Columbia, argued before the Supreme Court of British Columbia in 2010, appealed ultimately to the Supreme Court of Canada and ruled on November 10, 2016. We find that smaller classes can improve teacher-student interactions and individualized instruction, decreasing time spent on discipline issues, leading to better student behaviour, attitude, and efforts. Smaller classes generally have greater advantages for younger students, and effects are more observable in class sizes of less than 20. Small classes may shrink achievement gaps, decrease dropout rates, and increase high school graduation rates, and appear to enhance academic outcomes, particularly for marginalized groups. Researchers have detected class size effects many years later. Small classes have been found to boost teachers’ morale and job satisfaction. While some studies have found effects at the secondary and post-secondary level, results are generally inconclusive at this level. Finally, some researchers have argued that class size reductions are an inefficient use of funds which might be better spent elsewhere in the system. The paper concludes with a brief reflection on the process of providing this research for Supreme Court case.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.088
GPT teacher head0.417
Teacher spread0.330 · 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 designObservational
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

Citations11
Published2021
Admission routes3
Has abstractyes

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