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Record W2113832833 · doi:10.1017/s0272263114000369

ENGAGEMENT PORTRAITS AND (SOCIO)LINGUISTIC PERFORMANCE

2014· article· en· W2113832833 on OpenAlex
Françoise Mougeon, Katherine Rehner

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 Second Language Acquisition · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsPortraitSociolinguisticsLinguisticsPsychologySociologyVisual artsArt

Abstract

fetched live from OpenAlex

This study considers, both transversally and longitudinally, advanced second language (L2) learners’ profile portraits, how these correlate with their sociolinguistic and linguistic performance, and how changes in these portraits over time connect to changes in sociolinguistic performance. The results show a strong correlation between high degrees of learner engagement, as captured in the profile portraits, and the three measures of sociolinguistic and linguistic performance. The longitudinal data point to an increase over time both of levels of engagement and of use of informal sociolinguistic variants. By measuring the impact of learners’ evolving engagement on their use of sociolinguistic variants as they progress to a more advanced level of proficiency in their L2, the present study shows that an index of engagement can usefully summarize the multiple effects captured by the learner profile portraits and can shed light on rates of use of certain forms.

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)0.001
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 score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.055
GPT teacher head0.441
Teacher spread0.386 · 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