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Record W4411395778 · doi:10.5539/ijel.v15n4p1

Upon My Going into a Coffee-House Yesterday, and Lending an Ear to the Next Table. A Corpus-Based Exploration of Coffee House Dialogues and Their Discursive Practices in Late 17th and Early 18th Century England (1662–1712)

2025· article· en· W4411395778 on OpenAlexvenueno aff
Ersilia Incelli

Bibliographic record

VenueInternational Journal of English Linguistics · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsYesterdayArgumentation theoryPopularityPolitenessConversationPeriod (music)PoliticsAssertivenessSociologyLinguisticsPoint (geometry)LiteratureAestheticsPolitical sciencePsychologyLawSocial psychologyArtPhilosophy

Abstract

fetched live from OpenAlex

This research presents a corpus-based study which examines various speech-related written genres from the period 1662–1712. The collected texts, comprising transcribed coffeehouse dialogues, plays, poems, and trial proceedings, reflects the popularity of public coffeehouses in England, renowned as social spaces where people gathered news and debated ideas on politics, religion, science, literature, travel and other matters. Although coffeehouses have been studied from the historical, social theorist point of view (Habermas, 1989), this research adds linguistic insight into the experience of these public spaces. Hence, the aim of the study is to explore linguistic features relevant to the socio-historical and pragmatic aspects of the texts, focusing on speech acts, politeness strategies, conversation principles, hedging and assertive utterances. Data retrieved so far reveal a significant tension in the supposed discursive practices. The idea of the coffeehouse as a peaceful place of rational and reasoned argumentation contrasts sharply with linguistic evidence which shows coffeehouse conversations as not always so civil.

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)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.042
GPT teacher head0.301
Teacher spread0.259 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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