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Record W2059865591 · doi:10.1111/eie.12031

Beyond initial transition: An international examination of the complex work of experienced literacy/english teacher educators

2013· article· en· W2059865591 on OpenAlexafffundabout
Clare Kosnik, Pooja Dharamshi, Cathy Miyata, Yiola Cleovoulou

Bibliographic record

VenueEnglish in Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLiteracyPedagogyTeacher educationSociologyIdentity (music)Work (physics)Critical literacyEngineering

Abstract

fetched live from OpenAlex

This article reports on a study of 21 mid‐career and senior literacy/English teacher educators in four countries: Canada, the United States (), the United Kingdom (), and Australia. Three main themes are discussed: identity (re)construction; knowledge development (e.g. of pedagogy; current literacy practices); and reconceptualisation of their work (courses and research). The literacy/English teacher educators had moved beyond the struggles of novice teacher educators; however, they still experienced a number of tensions. They had moved beyond identifying with and as a classroom teacher but felt that they needed to remain connected to teachers because their research is conducted in schools. They still felt less valued by their colleagues who were not actively involved in teacher education, not because they were novices, but because of their close involvement in schools. They found communities of literacy/English teacher educators beyond their university. All argued that they must continue to expand their knowledge in a number of areas but they see their continuous growth as a strength not a short‐coming. By mid‐career many created a synergy among their research, teaching, and service.

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)0.007
metaresearch head score (Gemma)0.012
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 score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0110.008
Scholarly communication0.0100.004
Open science0.0010.009
Research integrity0.0010.003
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 head0.048
GPT teacher head0.376
Teacher spread0.328 · 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

Citations24
Published2013
Admission routes3
Has abstractyes

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