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Record W4416401069 · doi:10.1075/scl.122.14joa

Examining coherence and cohesion errors in writing Catalan as an additional language

2025· book-chapter· en· W4416401069 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

VenueStudies in corpus linguistics · 2025
Typebook-chapter
Languageen
FieldPsychology
TopicSecond Language Acquisition and Learning
Canadian institutionsUniversité de MontréalUniversité TÉLUQ
Fundersnot available
KeywordsCatalanCohesion (chemistry)Coherence (philosophical gambling strategy)PerceptionError analysisLanguage proficiency

Abstract

fetched live from OpenAlex

Abstract This study presents an analysis of a corpus of short texts written by French-speaking students of Catalan as an additional language. The research showed the frequent occurrence of errors of coherence and cohesion, though frequencies varied somewhat according to the student’s prior knowledge of other languages in writing. These results were the basis for online exercises featuring brief grammatical explanations for each error. The exercises were tested on French-speaking students of intermediate-level Catalan, who also answered an online questionnaire about their perceptions of the exercises as well as their use of first and additional languages. Scores and questionnaire responses together suggest that combining corpus-based error analysis and online exercises anticipating these errors may constitute a feasible and effective methodology to enhance language learning.

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)0.000
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.560
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.069
GPT teacher head0.378
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