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Record W2791822922 · doi:10.5539/ijel.v8n4p106

Pauses and Hesitations in Drama Texts

2018· article· en· W2791822922 on OpenAlexvenueno aff
Nawal Fadhil Abbas, Rua'a Tariq Jawad, Maysoon Tahir Muhi

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
FundersUniversity of Baghdad
KeywordsContext (archaeology)Value (mathematics)Computer scienceLinguisticsDramaState (computer science)HomecomingComprehensionHistoryLiteraturePhilosophyArtAlgorithm

Abstract

fetched live from OpenAlex

Pauses and hesitations are phenomena that can be found in speech. They can help both the speaker and the hearer, due to the functions they have in a dialogue. Their occurrence in speech has a value that they make it more understandable. In this regard, the researchers intend to critically examine the pauses and hesitations used in the two texts as well as their functions. The present paper aims to identify the types of pauses and hesitations used by Pinter’s The Homecoming and Baker’s Circle Mirror Transformation as well as the functions they serve and to compare both playwrights in this regard. To do so, the sequential production approach of turn taking, in combination with the contributions of some scholars who state the multifunctional use of pauses and hesitations, has been used. The findings of the present study show that pauses and hesitations do not exist arbitrarily in speech but they are found to serve certain functions depending on the context in which they occur. Regarding the two selected extracts, it is noticed from the comparison that the two writers do not use pauses and hesitations equally. Baker uses them more frequently than Pinter due to the context in which they are used which requires using pauses to aid comprehension.

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)0.000
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.319
Teacher spread0.285 · 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 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

Citations3
Published2018
Admission routes1
Has abstractyes

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