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Record W4220828100 · doi:10.5539/ijel.v12n3p65

The Language of Diplomacy in Inaugural Speeches: Roberta Metsola’s Speech as the New President of the EU Parliament

2022· article· en· W4220828100 on OpenAlexvenueno aff
Francesco Pierini

Bibliographic record

VenueInternational Journal of English Linguistics · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPresidencyParliamentRhetorical questionPresidential systemPolitical sciencePoliticsDiplomacyForeign policyContext (archaeology)Construct (python library)Media studiesSociologyDiscourse analysisPublic relationsLinguisticsLawHistory

Abstract

fetched live from OpenAlex

The study of inaugural speeches is fairly consolidated, especially if we refer to the analysis of the speeches of American presidents. Much less is available on the subject when we delve into lesser-known presidential figures, such as the presidents of European institutions. The analysis of the speeches of American presidents through the methodology of discourse analysis has helped to reveal their political intentions, their way of persuading listeners, building trust and empathy with the public, but also reaffirming their policies and measures relating to the economy, foreign affairs and social issues. In this paper I will focus on the new President of the European Parliament Roberta Metsola, elected on January 18, 2022. We are therefore in a completely different context, since the two forms of presidency are different in terms of roles, tasks and powers granted. Metsola’s inaugural speech will be analysed from a Discourse Analysis perspective, with a focus on lexical choice, personal pronouns and rhetorical figures to show how she plans to construct the image of the new presidency of the EU parliament and her intended objectives. The paper analyses how those who work in institutions such as the EU try to convey political messages, maintain or change the point of view of their public on certain issues, and understand whether they tend to conform to the consolidated structural and linguistic protocols that characterize their role or whether they (may) lapse into discursive practices that sometimes seem trite and worn-out.

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)0.057
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.933
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.057
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 science0.0020.000
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 head0.016
GPT teacher head0.323
Teacher spread0.307 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicEuropean Union Policy and GovernanceFrench-language works237,207