Identity and writing: the discoursal ethos in academic texts in English as an Additional Language
Bibliographic record
Abstract
Entering higher education poses many challenges for students, especially with regards to the production of written genres in the academic field. In the case of internationally educated nurses, immigrants, seeking their qualification and professional insertion in the Canadian health system, academic failure can have dramatic consequences. This work is an investigation about the discursive strategies of positioning (stance) in the production of texts in the academic domain, of a group of 7 health professionals taking a bridging program - a Bachelor of Nursing - at York University in Toronto / CA. The challenges represented by the demands of the intense production of texts from academic genres in the English language in this program, a language that these professionals know as a second language or, as we prefer, an additional language, are incomparable to the previous experience in their training as nurses. Our work is an excerpt that seeks to understand their textual production, in comparison with the publications of experienced authors from the academic-professional community of Nursing. We seek, as theoretical and methodological supports for this endeavor, assumptions of Critical Applied Linguistics (MOITA LOPES, 2006; PENNYCOOK 2001, 2007; RAJAGOPALAN, 2003), of the current theories that connect Language, Writing and Identity (HYLAND, 2005; IVANIC, 1998; NORTON, 2013; SIGNORINI, 1998), Argumentation Theory (AMOSSY, 2016; 2020) and the resources of corpus Linguistics tools (CALLIES, 2015; DUTRA, ORFANÓ, ALMEIDA, 2019; GILQUIN, GRANGER, PAQUOT, 2007; GRANGER, 2015). The results suggest that the participants approach, in several points, the practices of the academic-professional community of Nursing, in their discoursal practices in academic writing, but the points of divergence point to ways for the formation of foreign students in the learning of these genres. Above all, the results reveal the delicate balance between impersonality and visibility of the discoursal ethos, both of the participants and of the experienced writers of this community.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.036 |
| Scholarly communication | 0.018 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".