Research Note: The silenced assistant. Reflections of invisible interpreters and research assistants
Bibliographic record
Abstract
Abstract Given the increased attention in anthropology and human geography to the positionality and reflexivity of researchers completing fieldwork in foreign countries, it is surprising that we still know relatively little about how research assistants and interpreters are positioned in the field and their own concerns, constraints and coping mechanisms. This article, based on in‐depth interviews with local interpreters/research assistants in Vietnam and China, working alongside Western doctoral students researching upland ethnic minority populations, provides space for the assistants' voices. While reflecting upon their own time in the field, we see how the positionalities of these individuals can have rather unexpected consequences. Furthermore, the assistants' analyses of particular events, as well as their take on the best way to proceed in specific circumstances can be at odds with that of their employers, and negotiated coping strategies have to be found. The article concludes with advice from these assistants regarding how future assistants can make the best of their position, and what foreign researchers need to consider in fostering constructive working relationships.
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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 | 0.015 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.018 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".