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Record W4362714731 · doi:10.53103/cjlls.v3i2.91

An Analysis of the Problems in English Sentences by Francophone Learners of English; The Case of Premiere and Terminal Students of the Far North Region of Cameroon

2023· article· en· W4362714731 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Language and Literature Studies · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Linguistics, Cultural Analysis
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsFrenchFace (sociological concept)LinguisticsSyntaxStructuralism (philosophy of science)Foreign languageCode-switchingMathematics educationPsychologyComputer sciencePhysicsPhilosophy

Abstract

fetched live from OpenAlex

This research work sets out to investigate on the problems Francophone learners face in an attempt to study English as a Foreign Language. Premiere and Terminale were randomly selected in the Far North Region of Cameroon for this study. Data was collected through an essay writing test administered to students. Data was analysed quantitatively and qualitatively within the framework of Error Analysis and Structuralism. The findings revealed that, the learners’ problems range from omission of words, addition of unnecessary elements, mechanics, syntax, code mixing and code switching. The findings further proved that, these abysmal problems are caused by both teachers and students. It is in this regard that this article has suggested solutions which could assist both students and teachers to overcome these challenges.

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)0.001
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 score0.340
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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