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Record W2144956395 · doi:10.1080/13598660903474171

Negotiating spaces: the in-betweeness of becoming a teacher

2010· article· en· W2144956395 on OpenAlexaff
Anita Sinner

Bibliographic record

VenueAsia-Pacific Journal of Teacher Education · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPracticumSituatedNegotiationTeacher educationPedagogyPerspective (graphical)SociologyProfessional developmentService (business)Mathematics educationPsychologySocial scienceComputer science

Abstract

fetched live from OpenAlex

Pre-service teachers move through multiple learning communities during teacher education programs, arguably emerging as authentic insiders in teaching culture. In this case study, a critical perspective is offered by Ann, a First Nations learner who described her experience of teacher education, and how she came to question different aspects of her university program and practicum assignment which challenged her understandings of self. The experiences of pre-service teachers like Ann are often hidden from view, and what they perceive as shortcomings in programming are often unseen within institutional contexts. Ann articulated numerous gaps that still reside within teacher culture despite structures that are in place to address such gaps. The situated knowledge of pre-service teachers can offer alternative perspectives to guide the future of teacher education by drawing attention to shifts underway among students that will change the nature of professional 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)0.012
metaresearch head score (Gemma)0.019
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0310.067
Scholarly communication0.0200.026
Open science0.0030.025
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0070.001

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 head0.072
GPT teacher head0.385
Teacher spread0.313 · 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
Published2010
Admission routes1
Has abstractyes

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