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Record W4250864689 · doi:10.1002/9781405165396.ch43

Dialogic Approaches

2017· other· en· W4250864689 on OpenAlexaff
Michael Sider

Bibliographic record

Venuenot available
Typeother
Languageen
FieldSocial Sciences
TopicRussian Literature and Bakhtin Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsDialogicObject (grammar)Meaning (existential)LinguisticsRepresentation (politics)Context (archaeology)TextualitySociologySpoken languagePsychologyEpistemologyPhilosophyHistoryLaw

Abstract

fetched live from OpenAlex

Introduced into Romantic studies by Don H. Bialostosky, the term ‘dialogic’ has its source in the writings of the Russian theorist, Mikhail Mikhailovich Bakhtin (1895–1975). ‘Dialogic’ literally means ‘characterized by dialogue’, and Bakhtin places the concept of dialogue at the centre of his work on language and textuality. For Bakhtin, the act of communication between two people at a specific moment in a particular place is a model of the way all language depends for meaning on its social context. He argues that words are traditionally treated as their own direct expressions, encountering in their attempt to make meaning only the object they seek to represent. But this seemingly direct relationship between a word and its object is mediated by other words which impinge on the attempt at representation. In ‘Discourse in the novel’, Bakhtin asserts that every word finds the object at which it is directed already ‘overlain with qualifications’ by ‘alien words that have already been spoken about it’ (p. 276). A word is shaped by dialogic interaction with the alien words that are already in its object, just as speakers shape their words in dialogue as rejoinders to what has been said and what they anticipate will be said. Although the communicative aspect of language is ‘regularly taken into account when it comes to everyday dialogue’, Bakhtin insists that ‘every other sort of discourse’ as well is ‘oriented toward an understanding that is responsive’ (p. 280). Thus, the responsiveness of dialogue stands as an image of the doubleness of all language in Bakhtin, where the word is directed not only toward its object, but also toward what other people have said and are saying about this object.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0090.028
Scholarly communication0.0130.013
Open science0.0030.012
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0360.006

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 head0.117
GPT teacher head0.329
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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