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Record W2735220423 · doi:10.5539/ijel.v7n4p8

Investigation of Speech Acts of the Provisional Agreement of Intent

2017· article· en· W2735220423 on OpenAlexvenueno aff
Muhammad S. Shehadeh, Mahmud Wardat

Bibliographic record

VenueInternational Journal of English Linguistics · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsPolitenessPerspective (graphical)Rank (graph theory)AgreementOrder (exchange)PsychologySocial psychologyLinguisticsSociologyBusinessComputer scienceMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

This study investigated the provisional agreement of intent or the so called (Atwa) as a means of reconciling tribal disputes and conflicts from a socio-pragmatic perspective. The data consisted of forty provisional agreement documents on car accidents occasions, three video-recorded interactions and information collected via personal contacts with twelve interlocutors. The video-recorded materials and documents were categorized in accordance with politeness speech acts. The interviews concentrated on the personal details of the interlocutors in order to specify the main characteristics of those people and why they were chosen for this mission. This research finds out that frequently exchanged politeness strategies in the provisional agreement interaction include request, apology, honorifics, offering, compliment and thanking. Additionally, the researchers also found out that age, level of education, social rank, religion and socio-economic status were the sociolinguistic variables behind choosing the interlocutor.

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)0.022
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: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.067
GPT teacher head0.316
Teacher spread0.250 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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