Bibliographic record
Abstract
For a very young but steadily developing subfield of Translation Studies such as the translation of comics it seems only natural to look to other research areas within the discipline for inspiration and research methods. This is also one of the aims of the present article, which will attempt to point to certain similarities between comics translation and the subdiscipline of Translation Studies known as AVT (Audiovisual Translation) and the field of subtitling in particular. Both films and comic books are multimodal texts based on the interplay between the verbal and the visual. What is more, both films and comic books are primarily based on dialogue, which is nevertheless transcribed and communicated in writing in both subtitled films and translated comics. Text will, in both cases, usually appear in clearly specified areas, that is at the bottom of the screen (with some exceptions) in subtitled films, and in speech balloons (with some exceptions) in the case of comics. Furthermore, text may be condensed due to the existence of spatial and technical constraints, such as the limited number of characters that may appear at the bottom of the screen or the size of speech balloons and the type of the lettering employed in the case of comics. It is particularly the latter aspect, that is textual condensation related to both spatial constraints and the multimodal character of comics, that the article will focus on, investigating the first Polish translations of Calvin and Hobbes comic strips created by the American cartoonist Bill Watterson.
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 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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".