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Record W2558320435 · doi:10.7202/1038605ar

The Struggle for Teacher Professionalism in a Mandated Literacy Curriculum

2017· article· en· W2558320435 on OpenAlexaffvenue
Marsha Costello, David Costello

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsCurriculumConsistency (knowledge bases)FidelityContext (archaeology)AutonomyLiteracyPedagogyResistance (ecology)PsychologyMedical educationMathematics educationPolitical scienceMedicineComputer science

Abstract

fetched live from OpenAlex

This article reports on a study investigating how elementary teachers experienced the literacy initiatives that have been implemented in schools across PEI over the past five years. Such initiatives included the implementation of standardized instructional and assessment materials across the board and the emphasis on consistency of program use, reporting, and evaluation. Data were gathered through an online survey and interviews. Throughout this study, issues of professionalism, emotional impact, and teacher resistance were explored. This article focuses specifically on the issue of teacher professionalism and its relationship with prescribed curriculum. Findings suggest that professionalism is challenged when teachers attempt to adhere to the fidelity of program processes. However, fidelity to the purpose of a program would allow for teacher decision-making and autonomy within the context of any given program or practice.

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)0.017
metaresearch head score (Gemma)0.042
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 score0.017
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.042
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0080.007
Scholarly communication0.0050.002
Open science0.0010.008
Research integrity0.0020.005
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 head0.538
GPT teacher head0.544
Teacher spread0.006 · 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

Citations5
Published2017
Admission routes2
Has abstractyes

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