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Record W2464172954 · doi:10.1177/105678791302200101

Revisiting Ontario Teachers’ and Students’ Perceptions of Large-Scale Reform

2013· article· en· W2464172954 on OpenAlexaffabout
Thomas G. Ryan, Yee Han Peter Joong

Bibliographic record

VenueInternational Journal of Educational Reform · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsNipissing University
Fundersnot available
KeywordsCurriculumScope (computer science)Scale (ratio)Professional developmentPerceptionSample (material)Curriculum developmentPedagogyTeacher educationMathematics educationPolitical scienceMedical educationPsychologySociologyMedicineGeographyComputer science

Abstract

fetched live from OpenAlex

Within the following text, educational reform is examined to reveal how and to what extent Ontario secondary teachers (n = 87) have implemented educational changes that had a direct impact on students (n = 396), themselves, and curriculum. Our mixed methods data, while limited in scope, indicated that secondary school teachers were largely content with in-service professional development, resource supplies, and leadership. These new outcomes marked a swing away from the discontent noted in research completed in 2003, as positive indications were found in curriculum planning, teaching, student evaluation, reporting, technology, and the delivery of special education programs. Some areas, such as special education programming, were still viewed as problematic, yet sample teachers were able to support the reforms even though changes required additional planning time and new knowledge in the areas of assessment and technology.

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)0.010
metaresearch head score (Gemma)0.023
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 score0.131
Threshold uncertainty score0.446

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.008
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.386
Teacher spread0.357 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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