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Record W2159715782 · doi:10.5539/ijel.v3n4p101

A Psycholinguistic Justification of Dictation in TEM-4

2013· article· en· W2159715782 on OpenAlexvenueno aff
Lianbing Yao

Bibliographic record

VenueInternational Journal of English Linguistics · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Linguistics and Language Studies
Canadian institutionsnot available
FundersChina West Normal University
KeywordsDictationPsycholinguisticsCompetence (human resources)LinguisticsPsychologyLinguistic competenceComputer scienceCognitive psychologySocial psychologySpeech recognitionPhilosophyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Dictation is an important way to check the examinees’ language competence. To examine the examinee in this way, there must be some theoretical basis, and to prepare for it, there must also be some ways. This essay tries to look into the issue from the previous two aspects. We especially borrow the theories in psycholinguistics in dealing with the justification of dictation in TEM-4.

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 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)0.000
metaresearch head score (Gemma)0.080
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.937
Threshold uncertainty score0.928

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.080
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 head0.023
GPT teacher head0.276
Teacher spread0.253 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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