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Record W405418585 · doi:10.3726/978-3-0352-0010-2

Exterritorialité, énonciation, discours : approche interdisciplinaire

2010· book· fr· W405418585 on OpenAlexaboutno aff
Héliane Kohler, Juan Manuel López Muñoz

Bibliographic record

Venuenot available
Typebook
Languagefr
FieldComputer Science
TopicLinguistic Studies and Language Acquisition
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

Concept forge par le philosophe et sociologue Georg Simmel, l'exterritorialite designe le contexte de l'etranger - celui qui est dans une situation decalee, - entre-deux -, sur le seuil, renvoye a une alterite. Ayant trait a la mobilite et au changement, l'exterritorialite est d'ordre spatial, linguistique, culturel, identitaire... Traiter une telle question, c'est aussi prendre en compte l'enonciation et le discours. Souhaitant engager un dialogue interdisciplinaire, cet ouvrage s'interesse a differents genres de discours (litteraire, mediatique, testimonial, socioculturel, publicitaire...) analyses a la lumiere des nouveaux paradigmes epistemologiques et parametres socio-economico-culturels. Tout en cherchant a relever les differentes figures de l'exterritorialite, ce travail collectif vise a reflechir sur la question et a cerner ses fonctions. Quels sont les comportements enonciatifs et discursifs des locuteurs en contexte exterritorial et en situation interculturelle ? Comment les ecrivains - venus d'ailleurs - traitent le probleme de l'identite et percoivent leur alterite ? Comment est aborde le contexte exterritorial par le discours televisuel ? Il s'agit de quelques-unes des questions presentees lors du colloque qui s'est tenu a l'Universite de Cadix en 2008, reunissant des chercheurs d'Espagne, France et Canada, provenant de differents champs disciplinaires (analyse du discours, communication, litterature comparee, langues et litteratures etrangeres...).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.734
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.277
Teacher spread0.258 · 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
GenreOther

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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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