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Enregistrement W2483027944 · doi:10.1075/z.107.09jor

Some discourse patterns and signalling of theassessment-basis relation

2001· book-chapter· en· W2483027944 sur OpenAlex
Michael P. Jordan

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Notice bibliographique

RevueJohn Benjamins Publishing Company eBooks · 2001
Typebook-chapter
Langueen
DomainePsychology
ThématiqueLanguage, Metaphor, and Cognition
Établissements canadiensQueen's University
Organismes subventionnairesnon disponible
Mots-clésRelation (database)Basis (linear algebra)SignallingComputer scienceMathematicsMathematical economicsData miningGeometry

Résumé

récupéré en direct d'OpenAlex

Editors’ introduction As noted in the Introduction, we can focus on the patterns of text from two broad, related perspectives: in terms of repetition and of conjunction. A number of the papers in this collection combine these two perspectives, though often with a greater emphasis on one: for example, Darnton explores repetition, but in the context of Matching conjunctive relations, while Thompson & Thompson identify patterns of repetition primarily in order to discuss the conjunctive relations that they signal. Jordan concentrates solely on conjunction, since he is concerned with a relation which does not depend on repetition: that of Assessment and Basis. Assessment in Jordan’s terms is related to the concept of evaluation, the expression of an opinion about something, but is rather broader. An assessment may be made through thinking (making a deduction, or holding and/or expressing an opinion); but it may also be made through doing. An action taken in response to a situation or event constitutes an assessment of that situation. For example, if we see black clouds gathering as we sit down for a picnic in the countryside, we may assess it by thinking ‘It looks like rain’ or by expressing annoyance. But our assessment may equally take the form of getting out our umbrellas or abandoning the picnic. Thus the following three sentences all have two clauses in an Assessment-Basis relation, although the form of the assessment is clearly different in each case: Assessment Basis We predicted rain because it clouded over We were annoyed because it clouded over We went home because it clouded over Assessment–Basis is obviously close to a Cause–Effect relation, especially in cases like the third sentence (our going home was caused by the imminent rain); but Jordan argues that the most satisfactory way of distinguishing between them is in terms of conscious response vs. unwitting or mechanical outcome. Thus, in contrast to the examples of Assessment-Basis above, the following would be a Cause–Effect relation, since the temperature does not ‘decide’ to fall: Effect Cause The temperature fell because it clouded over. Basis in Jordan’s approach is generally straightforward: it is the reason or grounds for the Assessment. Jordan also outlines other elements that may appear in the text when an Assessment–Basis relation is constructed: the Topic (the entity, event or situation that is assessed — the weather in the examples above); and the Appraiser (the person who makes the Assessment — ‘we’ in the examples). Having established this broad, but internally coherent, definition of Assessment–Basis, Jordan then shows that it is a much more common and important means of linking chunks of text than might be expected — indeed, he argues that it can be seen as perhaps the most fundamental relation in any language. He explores in detail the ways in which the relation can combine with other types of conjunctive relations such as Cause–Effect, and can form part of larger patterns such as Problem–Solution. He also gives examples of chaining, where an Assessment–Basis can itself form the Basis for a further Assessment. He exemplifies different grammatical realisations of Assessment and Basis, and possible ways of signalling the relationship (though he points out that often there are no explicit signals). He discusses the various functions that Assessment–Basis can serve in text (e.g. how speakers may construct disagreements by expressing contradictory assessments and appealing to different bases); and he proposes that in order to understand more fully how the relation operates we need to look at issues such as what kinds of Basis are accepted or required in different contexts. It is interesting to consider the connections between the kind of text patterning that Jordan explores and those described by Hunston, by Thompson & Thompson and by Fries in their papers in this volume. Each deals with rather different kinds of patterning, though there are clear areas of overlap. Taken together, they indicate something of the complexity of the patterns of text; but they also reflect the variety of analytical approaches that have been developed to cope with this complexity.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Autre · Signal consensuel: aucune
Score de désaccord entre enseignants0,768
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,037
Tête enseignante GPT0,293
Écart entre enseignants0,255 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle