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Record W2969821148 · doi:10.7370/93189

Discourse Markers in English as a Target Language: The Use of so by Simultaneous Interpreters

2019· article· en· W2969821148 on OpenAlexfundno aff
Claudio Bendazzoli

Bibliographic record

VenueAcceda (Universidad de Las Palmas de Gran Canaria) · 2019
Typearticle
Languageen
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsnot available
FundersBrown UniversityUniversità degli Studi di FirenzeUniversità degli Studi di TorinoUniversité de FribourgUniversità di CataniaUniversità degli Studi di ParmaMenzies Centre for Australian Studies, King's College London, University of LondonUniversity of New South WalesUniversität WienUniversität HeidelbergUniversity of BristolSwansea UniversityInyuvesi Yakwazulu-NataliYork UniversityUniversität ZürichUniversità degli Studi di MilanoKing's College LondonUniversità di PisaHelsingin YliopistoVassar CollegeUniversity of DelhiUniversità degli Studi di Napoli "L'Orientale"University of WarwickAarhus Universitet
KeywordsLinguisticsDiscourse markerInterpreterComputer scienceNatural language processingPhilosophy

Abstract

fetched live from OpenAlex

This paper investigates the distribution of a particular discourse marker, i.e. so, in the target speeches produced by professional simultaneous interpreters while translating from Italian into English. The objective is to examine the possible effect on discourse marker distribution of specific situational norms that are in play in simultaneous interpreter-mediated settings. The analysis is both quantitative and qualitative, and is based on a parallel corpus of three medical conferences with Italian and English (native and non-native) speakers along with the corresponding simultaneous interpretations. All the occurrences of zero correspondence (30% of all the occurrences of so in target speeches) are examined in detail and grouped into different macro-categories. Subsequently, there is a discussion of possible reasons behind the interpreters' decision to add "sequentially dependent elements which bracket units of talk" (Schiffrin 1987: 31), with a view to contributing to the description of English in interpreter-mediated communication.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.418
Threshold uncertainty score0.969

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.361
Teacher spread0.339 · 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.

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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAcceda (Universidad de Las Palmas de Gran Canaria)Same topicInterpreting and Communication in HealthcareFrench-language works237,207