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Record W3011326275 · doi:10.37546/jalttlt37.4-2

JALT2013 Plenary Speaker article: How many hats do you wear?

2013· article· ja· W3011326275 on OpenAlexaff
Caroline Linse

Bibliographic record

VenueThe Language Teacher · 2013
Typearticle
Languageja
FieldSocial Sciences
TopicSociology and Education Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSupervisorLiteracyResidencePsychologyPedagogyMedical educationSociologyVisual artsPolitical scienceArtMedicineLaw

Abstract

fetched live from OpenAlex

This article provides a broad analysis of the many different hats teachers of young learners wear. How many of the following roles can you identify with: public relations director, cheerleader, choirmaster, literacy coach, assessment specialist, parent educator, storyteller, housekeeping services supervisor, artist in residence, child psychologist, justice of the peace, or diplomat? 本論では、年少者に教える教師が果たすたくさんの異なった役割について幅広く分析する。その役割は、広報部長、チアリーダー、聖歌隊指揮者、読み書き指導員、評価専門家、保護者指導教員、ストーリーテラー、家事サービス監督者、おかかえ芸術家、児童心理学者、治安判事、そして外交官など様々だが、あなたはそのうちいくつ特定できるだろうか。

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.080
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0800.022

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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2013
Admission routes1
Has abstractyes

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