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Record W7095395908

e-brief Heads of the Class: A Comparison of Ontario School Boards by Student Achievement

2015· article· en· W7095395908 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSchool Choice and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsStudent achievementTest (biology)Quality (philosophy)Student's t-testAffect (linguistics)Standardized testAchievement testAcademic achievement
DOInot available

Abstract

fetched live from OpenAlex

Does differing management of schools by Ontario school boards affect student outcomes? This e-brief uses the approach and data I developed in Johnson (2005, 2007) to answer that question. While my previous work provided a method for evaluating and comparing individual school performance based on student achievement, this study focuses on evaluating the performance of entire school boards. I conclude that there are significant differences among school boards in terms of student achievement. As a starting point, I employ data provided by Ontario’s standardized test results in reading, writing and mathematics in grades 3 and 6. These results, however, reflect both the quality of teaching at the school and the socio-economic characteristics of the school’s community. Schools where parents have lower socio-economic profiles will have fewer students meet or exceed expectations (herein referred to as a pass) regardless of teacher or administrator effort and ability. Adjusting test scores to remove the influence of these socio-economic factors (which explain about 40 percent of the variation among schools) yields measures of relative school performance that represent a school’s effectiveness. The relationship between a socio-economic index and a school’s adjusted pass rate is shown in Figure 1 for an illustrative group of Grade 3 schools. 1

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.056
GPT teacher head0.370
Teacher spread0.315 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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