Emergent identities in on-line discussions for second language learning. The Canadian Modern Language Review
Bibliographic record
Abstract
Abstract: In this article, issues of identity in second language (L2) leaming are examined by using discourse analysis and ethnographic observa-tions to analyze electronic bulletin board postings by ESOL students in a content-based class as they participated in discussions about gay rights and homosexuality. Drawing on notions of identity construction, community of practice, and participation frameworks, we demonstrate that as the students were engaged in the language and content of the lessons, they also selected multifaceted and complex alignments with their existing values and the values promoted in the course. In turn, their stances in the discussions could either encourage or discourage their participation and opportunities to use the L2. Eurther, in these on-line discussions, language socialization was uniquely facilitated by the affordances of computer technology. Resume: A l'aide de l'analyse de discours et de l'observation ethnographique, nous proposons d'examiner la question de l'identite chez les apprenants de langue seconde ayant participe, dans Ie cadre d'une classe axee sur Ie contenu, a des discussions electroniques sur les droits des homosexuels dans la societe modeme. En nous appuyant sur des notions liees a la cons-truction de l'identite, aux commimautes de pratique et aux cadres de partici-pation, nous demontrons que les apprenants, engages dans Ie langage et Ie contenu de la leqon, ont aussi adopte des positions complexes a facettes multiples vis-a-vis de leurs valeurs personnelles et de celles vehiculees dans Ie cours, De plus, nous avons constate que leurs prises de position dans les discussions exer^aient ensuite une influence sur leur participation en langue seconde et sur les occasions d'uhliser la langue cible. Nous montrons enfin comment la technologie a facilite la socialisation de la langue dans les discus-sions en ligne.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".