Bibliographic record
Abstract
Postsecondary institutions increasingly focus their efforts on internationalization, but foreign language faculty and language and literature departments are conspicuously absent from the great majority of these discussions (Knight 2006, Gerndt 2012). The emerging field of Business Language Studies (Doyle 2012) offers an important path to participating in these decisions and thus to helping shape the discussions about developing our students’ global and intercultural competencies. The purpose of this article is twofold. On the one hand, we will show how BLS aligns with recent pedagogical trends put forth by national associations (MLA, ACTFL, AAUC), underscoring the importance of showcasing its work not only within language departments, where it is often relegated a minor status, but on campus and in the larger community where students engage in project-based and community outreach work. On the other hand, we will demonstrate how deliberate BLS programming in the study abroad context provides a model of best practices that offers important opportunities for growing the field of BLS, and more importantly, gives students unprecedented access to the business world. A new study abroad program, Duke in Montreal, provides a case study for how to implement such a program.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.017 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".