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Record W7000884188

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

2018· dissertation· en· W7000884188 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2018
Typedissertation
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsStyle (visual arts)WishLexical itemTranslation (biology)
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.532
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.246
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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