Gazing and Typing Activities during Translation: A Comparative Study of Translation Units of Professional and Student Translators
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
The paper investigates the notion of Translation Units (TUs) from a cognitive angle. A TU is defined as the translator’s focus of attention at a time. Since attention can be directed towards source text (ST) understanding and/or target text (TT) production, we analyze the activity data of the translators’ eye movements and keystrokes. We describe methods to detect patterns of keystrokes (production units) and patterns of gaze fixations on the source text (fixation units) and compare translation performance of student and professional translators. Based on 24 translations from English into Danish of a 160 word text we find major differences between students and professionals: Experienced professional translators are better able to divide their attention in parallel on ST reading (comprehension) and TT production, while students operate more in an alternating mode where they either read the ST or write the TT. In contrast to what is frequently expected, our data reveals that TUs are rather coarse units as compared to the notion of ‘translation atom,’ which coincide only partially with linguistic units.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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