MétaCan
Menu
Back to cohort
Record W4362698628 · doi:10.5430/wjel.v13n5p299

An Analysis of Presuppositions in the Victory Speech of President Joe Biden

2023· article· en· W4362698628 on OpenAlexvenueno aff
Vikas Lathar, Jayashree Premkumar Shet, Christy Paulina J, S Vennila, S. Moorthi, Retna Mony R, D. Solomon Paul Raj, Aseda Fatima R., C. Divya

Bibliographic record

VenueWorld Journal of English Language · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCultural, Linguistic, Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPresuppositionUtteranceLinguisticsMeaning (existential)PsychologyContext (archaeology)PragmaticsCounterfactual thinkingEpistemologyPhilosophySocial psychologyHistory

Abstract

fetched live from OpenAlex

"Pragmatics is the study of the meaning of a speaker's utterance," according to Yule (1996:3).At the same time it’s the hearer, who deduces the meaning of the utterance from the context of what the speaker wants to convey. Speakers generally make indirect assumptions about the true picture of the situation in everyday status quo, and the meaning or comprehension of what is stated may be altered by the speaker's preconceptions (Haji, and Mohammed, 2019). On this note the notion of presupposition arises. Presupposition is defined as the speaker's implicit but communicated assumption. (Levinson, 1983) As a corollary, the intent of this present descriptive qualitative study is to investigate many types of presuppositions, their triggers and their relevance in Joe Biden's Victory Speech. Additionally, this discourse analysis research investigates what types of presuppositions, and their triggers are used by Biden, as well as it explores in depth the most prominent type of presupposition in the chosen speech. Yule's theory of presupposition classifies presupposition into six categories: existential presupposition, factual presupposition, lexical presupposition, structural presupposition, non-factual presupposition, and counterfactual presupposition. The study's data is comprised of statements that involve presupposition triggers. Levinson's list of lexical and syntactic triggers is adapted to identify presuppositions.The analysis of Biden’s speech has shown that the president heavily depends on lexical level triggers that have ranked first scoring eight hundred ninety-four occurrences, this means that this level triggers have effect on the speech. The topmost sub category trigger is Noun clauses that are the most prominent one with 683 occurrences. There were one hundred and eleven syntactic level triggers amongst which thirty-four of them are temporal clauses. It was also determined that, like every other speech, Biden's speech is laden with existential presupposition type (82.28%) and every other type of presuppositions has been identified in the president’s speech. The finding of a large number of triggers in this work would aid both linguistic and pedagogical domains.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.334
Teacher spread0.312 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueWorld Journal of English LanguageSame topicCultural, Linguistic, Economic StudiesFrench-language works237,207