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Record W2059902155 · doi:10.7202/019850ar

Studying Directionality in Simultaneous Interpreting through an Electronic Corpus: EPIC (European Parliament Interpreting Corpus)

2009· article· en· W2059902155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMeta Journal des traducteurs · 2009
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsParliamentEPICComputer scienceRomanceCorpus linguisticsLinguisticsNatural language processingArtificial intelligenceHistoryLiteratureArtPolitical scienceLawPhilosophyPolitics

Abstract

fetched live from OpenAlex

Parallel corpora have long been awaited in simultaneous interpreting studies in order to validate existing theories and models. The present paper illustrates the development of the European Parliament Interpreting Corpus (EPIC), an open, parallel, multilingual (English, Italian and Spanish), POS-tagged corpus of European Parliament source speeches and simultaneously-interpreted target speeches. The aim of the project is to study recurrent lexical patterns and morphosyntactical structures across all the possible language combinations and directions, and verify empirically whether different strategies can be detected when interpreting from a Germanic language into a Romance one and vice-versa, or between two Romance languages. EPIC is freely available on-line for the research community to use and contribute to.

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.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.669
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.004
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 head0.087
GPT teacher head0.408
Teacher spread0.321 · 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