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Record W2112119670

L'Interprétation Comme Reparation et Comme acte Menaçant pour la Face (FTA): (Im)poli envers qui?

2014· article· fr· W2112119670 on OpenAlexaff
Jean-Guy Mboudjeke

Bibliographic record

VenueLinguistica Atlantica · 2014
Typearticle
Languagefr
FieldHealth Professions
TopicInterpreting and Communication in Healthcare
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPolitenessPsychologyUtteranceLinguisticsFace (sociological concept)OffensivePoliteness theorySocial psychologyHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In this article, we use the theoretical frameworks proposed by Brown and Levinson (1978) and by Kerbraat-Orecchioni (1996, 2002) to reveal hybrid politeness strategies in the linguistic behaviour of African interpreters who figured in novels of the colonial period. The interpreters did not limit themselves to translating remarks that threatened the face of their listeners. They did nol hesitate to reprove those who offered rude responses, which they refused to translate in any case (reproval and refusal to translate both functioning as acts of linguistic impoliteness); nor did they hesitate to alter these remarks in order to make them more acceptable, less offensive, and less damaging for the face of their recipients (such transformation functioning as an act of reparation [Gaffman 1973], and equating to an act of politeness). That the same utterance is analyzed as an act of impoliteness (from the standpoint of the speaker) and as an act of politeness (from the standpoint of the hearer) reaffirms the nature of politeness, underscoring the role of point of view in the perception of the speech act. One might well ask: Polite (or impolite) for whom?

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)0.004
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.004

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 head0.116
GPT teacher head0.450
Teacher spread0.335 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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