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Record W2608200495

A Year of Living Pedagically: the First-Year Teaching Experience of Exchange Students

2017· article· en· W2608200495 on OpenAlexaffabout
Bruce Tucker

Bibliographic record

Venue2017 Conference of the Canadian Society for the Study of Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTimelineGeneral partnershipMathematics educationNarrativeChinaPedagogyCoherence (philosophical gambling strategy)ReciprocalPsychologySociologyPolitical scienceGeography
DOInot available

Abstract

fetched live from OpenAlex

Based on three years of experience in a Teacher Education Reciprocal Learning Program, which is a part of a SSHRC Partnership Grant Project between Canada and China, this paper will explore the relationship between international exchange programs and the transition from teacher candidates to professional educators through to the end of their first year of teaching. The paper will apply the principles of narrative inquiry, paying particular attention to the ways in which participants structure coherence into their stories of their early education, the disruption of their ideas about learning while abroad, and their integration back into Chinese school systems. The paper will present a qualitative analysis of data derived from extensive interviews and electronic conversations with 3 students in Chongqing, one student in Fuzhou and 5 students in Chengdu, field notes and journal entries. All of the participants completed their first year of teaching during 2015-2016, and the paper will report on the first phase of a projected three year timeline for classroom observations ending with the 2018-19 year.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.024
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0240.009
Scholarly communication0.0120.006
Open science0.0030.016
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.088
GPT teacher head0.399
Teacher spread0.311 · 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

Citations0
Published2017
Admission routes2
Has abstractyes

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