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Record W1712848793

The Compiling Methods for Pinyin Textbooks of Teaching of Chinese as a Foreign Language: A Case Study on the Textbook for Interesting Chinese Pinyin

2011· article· en· W1712848793 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStudies in literature and language · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEducational Reforms and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsPinyinPronunciationChinese speech synthesisChinese as a foreign languageSyllabusComputer scienceLinguisticsChinese charactersMathematics educationPsychologyArtificial intelligenceSpeech synthesisPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

On the basis of reviewing and summarizing the current situation of Chinese Pinyin textbooks and considering the gains and experiences in the compiling process of The Textbook for Interesting Chinese Pinyin, this paper is to propose that Chinese Pinyin textbooks should take the difficulties for foreign learners fully into account and attach importance to the interest and practicality of teaching materials. We suggest to draw up a syllabus for Chinese Pinyin so that the teaching materials can effectively put teaching of pronunciation and speech flow together.Key words: Pronunciation; Chinese Pinyin textbooks; Compiling; Principles and methods

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.039
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.429
Teacher spread0.378 · 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