Discourses of translation : festschrift in honour of Christina Schäffner
Bibliographic record
Abstract
Contents: Beverley Adab/Albrecht Neubert: Preface - Gregory M. Shreve: The Discourses of Translation. An Introduction - Mary Snell-Hornby: Metaphor As Metalanguage. On The Trials And Tribulations Of Terminology In Translation Studies - Andrew Chesterman: Reservations Concerning The Explanatory Power Of Norms - Kirsten Malmkjaer: What's The Point Of Universals, Then? - Albrecht Neubert: Breadth And Uniqueness In Translation Studies. Generality And Specifics Of Translation Processes - Ahmad Ayyad/Anthony Pym: Translator Interventions in Middle-East Peace Initiatives. Detours in the Roadmap? - Paul Chilton/Hongyan Zhang: Criticism across Cultures. Critical Discourse Analysis in China and the West - Chantal Gagnon: Speeches In Translation. A Canadian Context - Franz Pochhacker: Obama's Rhetoric In German. A Case Study Of Inaugural Address - Marilyn Gaddis Rose: A Translator's Agenda. Seamus Heaney and Buile Suibhne (Sweeney Astray) - Christiane Nord: Can Say You To Me - Organizing Relationships In Literary Translation - Michaela Wolf: At The Centre Of The Female Inferno - Elfriede Jelinek's Novel Lust In English Translation - Paul Kussmaul: How To Be Truly Faithful - The Translation Of Social Surveys - Candace Seguinot: Questions of Learning Objectives in Translator Training - Miriam Shlesinger/Tanya Voinova: Self-Perception of Female Translators and Interpreters in Israel - Peter A. Schmitt: CIUTI, Bologna, EMT - Approaches towards better T&I quality.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.041 | 0.013 |
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".