Community Interpreting and linguistics: A fruitful alliance? A survey of linguistics-based research in CI
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the first Critical Link Conference in Geneva Park, Canada, in 1995, Community Interpreting (CI) has experienced a dramatic change in both theory and practice. National and international conferences, seminars, courses, and workshops all around the world have made it possible for practitioners, trainers, and researchers to get together and discuss their views and exchange ideas. At the same time, an ever-growingflow ofpublications reflects the enormous activity in this field. Nevertheless, CI re- search is still farfrom being in the same category as infields such as conference interpreting or translation, and this is all the more so for linguistics-based CI research.As a researcher working in a department mostly involved with linguistics and related areas but with an increasing interest in cultural studies and translation studies, it is my intention to analyze and classify the contributions to CI conferences and the publications of CI papers using a linguistics-based methodology. To begin with, the evolution of linguistics and those sub-areas, which have had the greatest influence in the lastfew decades, will be briefly discussed, as will its methodologies. Secondly, an analysis will be presented of the characteristics and tools of linguistics-based CI research. And thirdly, conclusions will be drawn concerning the evolution, trends or gaps in CI research in general, and in linguistics-based CI research in particular.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it