Moving In-Between: The Interpreter as Ethnographer and the Interpreting-Researcher as Anthropologist
Bibliographic record
Abstract
My starting point in this article is the community interpreter who works in social, medical and legal settings, under specific conditions, confronting very delicate ethical problems. In search of a theoretical framework that accounts for the social roles and cultural identities of the community interpreter I began to re-read the German anthropologist and conference interpreter Heinz Göhring. His articles can be positioned between German Studies (‘Deutsch als Fremdsprache‘), intercultural communication studies (including cultural anthropology) and translation studies. I start out with his view of an ideal translator/ interpreter as cultural expert acting like a “mini-ethnographer” and try to go beyond Göhring by connecting his ideas to the concept of the critical ethnographer as model for a professional community interpreter. In this theoretical discussion I want to show how a synthesis of the framework proposed by Göhring and recent anthropological theories can be used for a new professional profile of the interpreter, not only in community settings but in general. Besides aspects concerning translation/ interpreting politics, I wish to foreground that a re-thinking of interpreter roles would/ should also affect translation/ interpreting pedagogy and research.
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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 | 0.041 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.025 | 0.051 |
| Scholarly communication | 0.020 | 0.024 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".