Bibliographic record
Abstract
The aim of this article is to contribute to the establishment of a sub-field of translation studies, namely a sub-field devoted to the research of intralingual translation. The article’s contribution to this project is both theoretical and empirical. In the theoretical part of the article, an already existing, five-partite typology of intralingual translation is reviewed and on certain points refined. The empirical part is taken up by three case studies, each representing a particular subcategory of intralingual translation. The first study investigates translation between two geographical dialects (American and British English), the second examines the rewriting of a specialized, pharmaceutical product summary into a register aimed at lay readers, and the third investigates the modernization of one of Shakespeare’s plays. A primary concern of the case studies is to chart the range and nature of the translation strategies employed in the transformation of source texts into intralingual target texts. Translation strategies are conceptualized as shifts in the article, and well-known concepts from translation studies are applied in the analyses. The analytical results reflect clear differences, but also certain striking similarities between the types of shifts manifested in the individual cases.
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 | 0.000 |
| 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".