Preparing Postgraduates for the Profession: Toward Translingual Pedagogical Practices in Advanced Graduate Student Writing Instruction in Germany
Bibliographic record
Abstract
Contributing to the literature on translingual pedagogies outside the US or Canada, this article discusses the design of a hybrid instructional format for advanced multilingual doctoral students and post-doctoral researchers offered by a bilingual writing center at a mid-sized university in Germany. Meant to prepare for future careers in academia and professional demands in different national, cultural, and linguistic environments, this format gives participants the opportunity to explore academic genres that tend to receive less attention in graduate education than journal articles, book chapters, or others needed to complete degree requirements. By the end of the course, participants will have a submission-ready portfolio including an academic CV, a job letter, a (sample) letter of recommendation, and teaching and diversity statements. To achieve these specific outcomes and to develop the advanced professional academic writing competencies needed in multicultural and multilingual contexts, participants will have to draw on their diverse linguistic backgrounds and prior experiences in these kinds of settings. Informed also by other recent theoretical and empirical work on translingualism and translingual pedagogies in global contexts, this format adopts the use of translation proposed by Horner (2017) to move beyond the monolingual and, to a lesser extent, the multilingual paradigms. While it has yet to be tested empirically, the design represents an alternative to more traditional (and usually monolingual) modes of instruction. This article concludes by discussing limitations and implications of the approach to translingual pedagogies taken here.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".