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Record W388254852

Outsourcing in-service education in Japan : Challenges and issues

2009· article· en· W388254852 on OpenAlexaboutno aff
Melodie Cook

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsYardstickDimension (graph theory)Hofstede's cultural dimensions theoryPsychologyMathematics educationPedagogyOutsourcingService (business)Teacher educationSociologyPolitical scienceSocial psychologyBusiness
DOInot available

Abstract

fetched live from OpenAlex

This paper examines a four-month program of pedagogical training for Japanese Teachers of English (JTEs) in Canada based on a yardstick provided for communicative language teaching (CLT) in-service education and training (INSET) programs for teachers who teach English as a foreign language (EFL). In particular, with the purpose of determining the overall effectiveness of the Canadian pedagogical program and offering recommendations for future ones, this study examines three dimensions of the four-month program: the program planning dimension, the program execution dimension, and the cultural dimension. Three paradigms are used to compare cultural and educational differences between Japan and Canada: the interpretation-based versus transmission-based culture paradigm (Wedell, 2003), the collectionist versus integrationist educational paradigm (Holliday, 1994a), and the routine/uncertain culture versus non-routine/certain culture paradigm (Sato, 2002). This qualitative study indicates that while the program meets almost all of the recommended criteria, especially in the execution dimension, a more thorough knowledge of Japanese educational culture and a re-examination of some assumptions on which the program is constructed may be useful to program planners and trainers in helping JTEs overcome barriers to incorporating CLT practices into their lessons.

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)0.008
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.632

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0090.004
Scholarly communication0.0060.005
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.063
GPT teacher head0.430
Teacher spread0.367 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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