Bibliographic record
Abstract
Based on a critical ethnographic research project, this paper is about the impact of becoming Black on ESL learning; that is, the interrelation between identity formation, identification, race, culture and second language learning. It contends that a group of French-speaking immigrant and refugee continental francophone African youths who are attending an urban Franco-Ontarian high school in south- western Ontario, Canada, enters, so to speak, a social imaginary, a discursive space in which they are already imagined, constructed, and thus treated as Blacks by hegemonic discourses and groups. This imaginary is directly implicated in whom they identify with (Black America), which in turn influences what and how they linguistically and culturally learn. They learn Black English as a second language (BESL), which they access in hip-hop culture and rap lyrical and linguistic styles. Conducted within an interdisciplinary framework, this critical ethnography shows that (ESL) learning is neither neutral nor without its politics and pedagogy of desire and investment. En se basant sur un projet de recherche ethnographique critique, l'auteur considère l'effet de devenir Noir dans l'étude d'anglais comme langue seconde (ESL), c'est-à-dire la corrélation entre la formation de l'identité, l'identification, la race, la culture, et l'étude de la seconde langue. Il s'agit d'un groupe de jeunes immigrants et réfugiés francophones venant d'Afrique et allant à une école secondaire de langue française dans un centre urbain du sud-ouest de l'Ontario, Canada. L'auteur soutient que ces jeunes, pour le dire, entrent dans un espace social, décousu, imaginaire dans lequel ils se sont déjà imaginés, composés, et donc traités comme des Noirs à cause d’un discours hégémoniques. Cet espace imaginaire est directement impliqué sur ceux avec lesquels ils s'identifient notament des Afro-américains et qui, à leur tour, influencent sur ce qu'ils apprennent en langue et en culture. Ils ont appris l'anglais des Noirs comme langue seconde (BESL) qu'ils ont appris par la culture hip-hop, les paroles et l'expression linguistique du Rap. Conduit dans un cadre interdisciplinaire, cette étude ethnographique critique souligne le fait que l'apprentissage de langue (ESL) n'est ni neutre, ni indépendant des politiques et de la pédagogie du désir et de l'investissement.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".