Linguistic Risk-Taking: A New Pedagogical Approach and a Research Program
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Linguistic risks are situations in which learners are pushed out of their comfort zone to use the target language in meaningful and authentic settings. This article outlines a novel pedagogical and research approach to language learning through linguistic risk-taking. I review the construct of linguistic risk from interdisciplinary perspectives and describe the context, rationale, and development of an innovative initiative for supporting French and English language learning at the University of Ottawa, the largest bilingual (English-French) university in the world. Data from 554 participants collected through a Linguistic Risk-Taking Passport, a tool allowing learners to self-report risk-taking patterns, propose additional risks, and add qualitative comments are analyzed to validate the approach. Avenues for transformation of the tool into a digital app and its relevance to other contexts and other languages are also discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it