Power And Privilege: An Exploration Of Decision-Making Of Interpreters
Bibliographic record
Abstract
This article presents the findings of a study conducted with Deaf and hearing American Sign Language (ASL) interpreters from Canada and the United States who interpret legal discourse and legal interactions. This qualitative research study was designed to explore constructs of power and power dynamics that emerge in interpreted interactions. Sixteen interpreters, with at least fifteen years of experience in legal interpreting participated in an on-line survey; nine also participated in focus groups. This study found intersections among power and privilege, interpreters' sense of agency, their conceptualization of the task of interpreting, and their training. Participants reported situations where the power dynamics between Deaf and hearing interpreting teams did not support effective interpretation and ultimately had a negative impact on the interaction. How interpreters conceptualize the task of interpreting appears to be a key factor in producing successful interpreted interactions where power is mediated via interpretation. Participants offered examples of how conceptualization of the task of interpreting by various participants in an interpreted interaction (e.g. self, team partner, consumers) impacts their decision-making in several ways: qualification for an assignment; how they function as a Deaf-hearing team; and, what strategies they use to create meaning-based interpretation. This study highlights that the interpreter's own awareness of power and privilege is a crucial pre-requisite to support active decision-making that facilitates effective interpretation.This study has implications for interpreter educators and interpreters, and while the focus is on interpreting in legal settings, results are applicable across settings.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".