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Record W2940983170 · doi:10.1111/lic3.12521

British laughter and humor in the long 18th century

2019· article· en· W2940983170 on OpenAlexaff
Eugenia Zuroski Jenkins

Bibliographic record

VenueLiterature Compass · 2019
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsLaughterComedyPoliticsScholarshipPolitenessFeelingAestheticsPower (physics)Rhetorical questionContext (archaeology)SociologyPsychologyLiteratureMedia studiesSocial psychologyHistoryLawPolitical scienceArt

Abstract

fetched live from OpenAlex

Abstract This essay offers an overview of recent scholarship on British humor, satire, comedy, and laughter in the long 18th century. It focuses on scholarship that asks what provoked laughter in the 18th century, how the ethics and morals of laughter were gauged and contested, and what the political and social effects of laughter were, particularly in the context of cultural change and political crisis. Studies of laughter and humor demonstrate that 18th‐century British culture was, in many ways, not characterized by codes of politeness and sociability. Satiric laughter proved a potent but unpredictable political instrument, particularly in cases of anti‐religious humor, as likely to undermine or exceed humor's political objectives as it was to realize them. Laughter also generated new publics that wrested moral authority from traditional seats of power. Humor's effects were as multitudinous as the formal and rhetorical techniques it employed to generate feeling in readers and audiences, and the field has benefitted from a variety of methodologies and critical frameworks to explore its complex cultural and political functions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.013
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.279
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2019
Admission routes1
Has abstractyes

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