MétaCan
Menu
Back to cohort
Record W2029446201 · doi:10.7202/029794ar

Translating Epistemic Adverbs from English into Spanish: Evidence from a Parallel Corpus1

2009· article· en· W2029446201 on OpenAlexvenueno aff
Noelia Ramón García

Bibliographic record

VenueMeta Journal des traducteurs · 2009
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsnot available
Fundersnot available
KeywordsGrammaticalizationLinguisticsModalExpression (computer science)Perspective (graphical)Contrastive analysisFunction (biology)Computer scienceModal verbArtificial intelligenceNatural language processingPhilosophyVerb

Abstract

fetched live from OpenAlex

The expression of modal meanings is an area of great complexity in the relationship between form and function in a single language and cross-linguistically. Modal adverbs in particular are considered to be problematic from a contrastive perspective due to their multifunctionality in English (Aijmer 2005). This paper is a corpus-based study of the expression of epistemic possibility by means of three common modal adverbs in English (certainly, probably, possibly) and the translational options chosen in Spanish for expressing those meanings. The aim is to identify trends in the translations of these epistemic adverbs that contribute to a better understanding of the various semantic functions that native speakers attribute to these units. The analysis shows that the omission of modal adverbs in the translations may be considered as an indicator of the degree of grammaticalization attained by these adverbs in English. The results provide useful information not only in the field of translator training and practice, but also in descriptive linguistics.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.048
GPT teacher head0.300
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations11
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueMeta Journal des traducteursSame topicLanguage, Metaphor, and CognitionFrench-language works237,207