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Implicit Curriculum

2018· other· en· W2993181592 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe TESOL Encyclopedia of English Language Teaching · 2018
Typeother
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCurriculumIdeologySocializationCurriculum theoryMathematics educationPedagogyAffect (linguistics)NormativeSociologyPsychologyCurriculum developmentPolitical scienceSocial psychology

Abstract

fetched live from OpenAlex

English as an international language (EIL) is not free from ideologies and worldviews that accompany the dominant English language. There are many underlying implicit curricula (such as L1 user norms, English‐only instruction, gender, class, or racial ideologies) that are being taught and learned, often unrecognized by the language learners, while learning the English language. These implicit curricula of various types of discrimination, socialization, and unstated rules, when accepted without question, can affect success in language learning and teaching. While previous studies have exposed various dimensions of the implicit curriculum in EIL, current research focuses on complex interconnectedness of different linguistic, cultural, social, and individual factors that are shaped and are shaping the implicit curriculum in and out of EIL classroom settings. Future research must be devoted to more explicit investigation of the impact of intersectionality of implicit curricula on language teaching and learning and to more innovative pedagogical practices that can disrupt such impact.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.201
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.008
GPT teacher head0.293
Teacher spread0.286 · 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