University researcher-instructor partnership: Co-learning of trans/plurilingual pedagogies for critical language awareness in French L2/Lx classrooms
Bibliographic record
Abstract
Abstract Drawing on trans/plurilingual approaches, this paper describes a collaborative action research project between an education researcher and two university instructors of French as a second or other language (L2/Lx) in Quebec, Canada to explore holistic and dynamic ways of L2/Lx education for critical language and cultural awareness. Valuing research as praxis, we examine our three-year interdisciplinary collaboration processes, describing how our various research expertise and theoretical orientations as well as our language learning and professional experiences shaped and facilitated our research partnership. Through vignettes from our professional learning community, we each articulate in our own voice the co-learning processes with one another and with students. Using the lenses of co-stance, co-designs, and co-shifts (Tian and Shepard-Carey 2020. (Re)imagining the future of translanguaging pedagogies in TESOL through teacher–researcher collaboration. Tesol Quarterly 54(4). 1131–1143), we captured moments of our emerging nuanced understanding of what and how trans/plurilingual practices supported more in-depth French learning and critical language awareness. As we translanguaged using a mix of English, French, and other languages, we also found ourselves constantly re/trans-languaging our disciplinary expertise and theoretical framings to negotiate our co-stances and practices. Through these transknowledging processes (Heugh 2021. Southern multilingualisms, translanguaging and transknowledging in inclusive and sustainable education. In Philip Harding-Esch & Hywel Coleman (eds.), Language and the sustainable development goals: Selected proceedings of the 12th Language and Development Conference, 37–47. Dakar, Senegal: British Council), we engaged in translingual reflexivity and expanded each other’s fields of vision, supporting more critical reflections and careful listening for transformative change.
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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 | 0.039 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.018 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.004 | 0.020 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".