Neurocognitive Aspects of Translation
Bibliographic record
Abstract
Translation is at the centre of many cognitive domains such as pedagogy, linguistic, pragmatic, neurosciences, and social cognition. This multi-domain aspect is reflected in the current models of translation. Recently, cognitive neurosciences have unraveled some brain mechanisms in the bilingualism domain, and it is quite logical to transfer such knowledge to the field of translation as well as the learning of translation. One interesting question is which non-linguistic cognitive and communicative processes are particularly involved in translation. Particularly, in translation, the author’s intentions have to be interpreted although they may not be explicitly stated in the text. These intentions have to be considered while rendering the text for the target public, a process for which it is also important to anticipate the target public’s prior knowledge of the subject and the extent to which the author’s aims and intentions have to be adapted in order to be correctly communicated in the other language. In neuroscience, being able to imagine another person’s mental state is known as having a Theory of Mind (ToM). This skill seems dissociated from the group of executive functions – though it is very dependent on the latter – and seems to rely on a large but individualized brain network. While translation is a widely investigated phenomenon at the micro-level, there is scarcely any research about the process of interpretation going on at the macro-level of text interpretation and rendering. Preliminary neuroscience experiments on the translations paradigm suggest that neurosciences can bring interesting data not only to linguistic but also to cognitive and social mechanisms of translation strategies.
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How this classification was reachedexpand
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".