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Record W2121031452 · doi:10.1558/cj.v20i2.215-336

Learning French Pronunciation

2003· article· en· W2121031452 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCALICO Journal · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Language Learning Methods
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPronunciationPhoneticsIntonation (linguistics)LinguisticsComputer scienceCurriculumPsychologyPedagogy

Abstract

fetched live from OpenAlex

Phonetics, intonation, and pronunciation are integral parts of language learning. However, they are not often an actual part of the content of language classes. One reason may be that teachers are not necessarily trained in phonetics and therefore are reluctant to make this component a part of their teaching. Another reason may be that the proper tools are not being used or that the proper tools are not being used appropriately in order to assist teachers and students in integrating phonetics into the curriculum. This article describes a two phase experiment that was conducted at the University of Ottawa using audiocassettes and multimedia while teaching French, specifically French phonetics, intonation, and pronunciation, to a group of low-intermediate level language students. The present study addresses three questions: (a) Are the receptive and productive skills of intermediate-level learners of French as a second language influenced by the explicit teaching of phonetic and prosodic elements? (b) if so, which delivery mode is the most effective to teach these elements: audio cassettes or multimedia? and (c) what are the students’ preferences with regards to these two delivery modes?

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.335
Teacher spread0.309 · 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