Bibliographic record
Abstract
Translation practices from the perspectives of identity performance, cultural mediation, historical reframing, and professional training Translating and interpreting are unpredictable social practices framed by historical, ethical, and political constraints. Using the concepts of situatedness and performativity as anchors, the authors examine translation practices from the perspectives of identity performance, cultural mediation, historical reframing, and professional training. As such, the chapters focus on enacted events and conditioned practices by exploring production processes and the social, historical, and cultural conditions of the field. These outlooks shift our attention to social and institutionalized acts of translating and interpreting, considering also the materiality of bodies, artefacts, and technologies involved in these scenes. Contributors: Raquel Pacheco Aguilar (Johannes Gutenberg University of Mainz), Ehsan Alipour (Allameh Tabataba'i University), Audrey Canalès (Université de Montréal), Paola Gentile (University of Trieste), Marie-France Guénette (Université Laval), Ellen Lambrechts (KU Leuven), Yuan Ping (Hangzhou Dianzi University), Marike van der Watt (KU Leuven), Wenqian Zhang (University of Leeds) This publication is GPRC-labeled (Guaranteed Peer-Reviewed Content).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.062 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".