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Record W7020670902

Metáforas gramaticales y coherencia en la conversación coloquial : primeras aproximaciones

2010· article· es· W7020670902 on OpenAlexfundno aff

Bibliographic record

VenueFAHCE-UNLP Institutional Repository Academic Memory (National University of La Plata) · 2010
Typearticle
Languagees
FieldArts and Humanities
TopicSpanish Linguistics and Language Studies
Canadian institutionsnot available
FundersUniversidad de Buenos AiresTrent UniversityNottingham Trent University
KeywordsContext (archaeology)Period (music)PoetryLinguistic change
DOInot available

Abstract

fetched live from OpenAlex

Presentamos en este trabajo el resultado de una investigación cualitativa, descriptiva acerca del rol de la metáfora gramatical en la conversación coloquial. El corpus utilizado para este análisis está formado por 52 conversaciones coloquiales entre estudiantes universitarios de entre 20 y 28 años de edad, que forman parte del corpus del proyecto ECAr (Español Coloquial de Argentina). Partiendo de las nociones de coherencia y metáfora gramatical de la Lingüística Sistémico-Funcional (Halliday, 1994, 2004) se han analizado los textos en busca de tramos que contengan dichas metáforas en cantidad significativa para luego compararlos con tramos en los que no se descubren gran cantidad de metáforas gramaticales. La comparación se efectuó sobre la base de una encuesta en las que se les pidió a un grupo de estudiantes universitarios que ordenen los tramos teniendo en cuenta cuáles se entendían mejor, y de la armonía cohesiva de todos los fragmentos; además se calcularon la densidad léxica y la complejidad gramatical de los fragmentos seleccionados. El análisis de los datos nos permitió descubrir que, en general, los fragmentos que contienen gran número de metáforas gramaticales son percibidos por los sujetos encuestados como menos coherentes, lo cual podría deberse a que tienen menor armonía cohesiva y gran densidad léxica.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.013
GPT teacher head0.241
Teacher spread0.228 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2010
Admission routes1
Has abstractyes

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