Interpretation as a Communicative Event: A Look through Hymes' Lenses
Bibliographic record
Abstract
In the last ten years, more researchers and practitioners have turned their attention to community interpreting. Issues of similarities and differences with other forms of interpreting, as well as recognition and prestige, have arisen. It is often the case that the standards of conference interpreting are blindly transferred to other forms of interpreting both for measurement and educational purposes. This blind transfer does not allow a full understanding of the complexities involved in community interpreting. Hymes' taxonomy of speaking is used to compare and analyze two interpreting events, one occurring in a community setting and the other in a conference one. The analysis suggests that there are more differences than similarities between the two settings. The differences point to a complex form of social interaction which needs attention in its own right.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.015 | 0.085 |
| Scholarly communication | 0.024 | 0.033 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 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".