MétaCan
Menu
Back to cohort
Record W7100001486

Exploring the Effects of First- and Second-Language Proficiency on Summarizing in French as a Second Language», in Canadian

2000· article· en· W7100001486 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsAutomatic summarizationAffect (linguistics)Second languageLanguage proficiency
DOInot available

Abstract

fetched live from OpenAlex

University students studying a second language are often required to sum-marize information they read or hear in that language. These learners bring with them a number of first-language summarization skills which may have an effect on how they acquire second-language summarization skills. What macrorules of summarization are actually affected by either first-language or second-language proficiency? According to the results of this study, both first-language summarizing skills and second-language proficiency affect second-language summarizing skills, except for inclusion of main ideas and amount of distortion which are more affected by first-language summarizing skills. Neither first-language summarizing skills nor second-language profi-ciency have an effect on combining within and across paragraphs and the use of macropropositions. Suggestions for teaching and future research conclude the paper. Les étudiants de niveau universitaire qui étudient une langue seconde ont sou-vent a ̀ résumer l’information qu’ils lisent ou entendent dans cette langue. Ces apprenants font preuve d’un nombre d’habiletés propres au résume ́ de texte dans leur langue maternelle qui pourraient avoir une influence sur la façon d’acquérir ces habiletés dans une langue seconde.Quellesmacrorègles propres au résume ́ de texte sont en fait influencées soit par la compétence en langue maternelle soit par la compétence en langue seconde? Selon les résultats de cette étude, ces deux facteurs ont une influence sur l’habilete ́ a ̀ résumer un texte dans la langue seconde, exception faite toutefois de l’incorporation des idées principales et du degre ́ de distorsion du message qui sont plus influ-encés par leur habilete ́ a ̀ résumer un texte dans leur langue maternelle. Ni la compétence dans ce domaine en langue maternelle, ni la compétence en langue seconde n’exercent une influence sur la combinaison de phrases au sein d’un paragraphe ou de plusieurs paragraphes, ou encore sur l’utilisation de macropropositions. Des suggestions quant a ̀ l’enseignement de ces habiletés et quant aux recherches a ̀ venir concluent cette étude.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2000
Admission routes1
Has abstractyes

Explore more

Same topicBotanical Research and ChemistryFrench-language works237,207