I Just Wish the World was Twice as Big and Half of it was Still Unexplored:\nAn Exploration of the Translation of Adjectives in Travel Guides
Bibliographic record
Abstract
As explored the world is, as Sir David Attenborough exclaims in his famous quote, as unexplored research on adjectives in translation is, let alone research on adjectives in translation within a specific genre, and what the effects and causes may be of particular (consistent) choices and/or shifts. Through a corpus of seven English source texts and seven Dutch target texts, the translation of adjectives in travel guides are explored. All texts are from the same publisher, Rough Guides, and they are divided into two subgenres: cities and countries. The cities are Barcelona, Istanbul and Rome, while the countries are Brazil, Canada, Kenya and Laos. Rough Guides is one of the frontrunners to develop a highly characteristic, personal style of writing, and is know for their clever style, where descriptive elements (such as adjectives) are used to portray wit, enthusiasm, and other characteristic traits. In total, 1,050 adjectives were collected from this corpus. The results showed that roughly twenty percent of all adjectives were not regularly translated in these travel guides, but either omitted or edited. The three most commonly used strategies in edited adjectives are: the replacement of adjectives with lexically deviant adjectives, the “emphasis change” strategy, and the “information change” strategy. The effect of these omitted and edited adjectives is that the target texts are more disconnected and flatter, and the specific style that Rough Guides is known for is diminished. Readers of the target text will also perceive the location differently, which may have further implications on their decisions to visit certain places. The results also showed that objective adjectives are more likely to be omitted, subjective adjectives to be edited, and objective adjectives to be regularly translated. This curiosity has led to the conclusion that the function of the target text is not to be strictly informative, but rather a blend of the three text functions: informative, expressive and appellative. It can also be speculated that the target audience was the reason behind these omitted and edited adjectives.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".