Culture Brokers, Advocates, or Conduits: Pedagogical Considerations for Deaf Interpreter Education
Bibliographic record
Abstract
In a qualitative review of interpretation and Deaf2 studies programs in Canada, some educators described their experiences teaching Deaf students. Most of the Deaf instructors had worked as Deaf interpreters (DIs). Given the challenges they faced as a DI, and in light of research concerning interpreters from other minority cultures, the conceptualization of their subjectivity should consider their ethnicity; perhaps the role of culture broker or advocate is appropriate in some settings. The inclusion of Deaf students in the programs led to many benefits, as described by the participants, including a heightened awareness of power, Freire’s (2004) conscientização, through awareness of praxis. Examples of Freire’s philosophy of education as being dialogic were also noted, as the Deaf students took on the role of teacher. However, educators might wish to reconsider practices that promote massification (Freire, 1974), such as assignments only in English and the Deaf interpreter serving in the role of a conduit.
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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 | 0.077 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.018 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".