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Record W2127874711 · doi:10.1177/147470490600400129

The First Joke: Exploring the Evolutionary Origins of Humor

2006· article· en· W2127874711 on OpenAlexaff
Joseph Polimeni, Jeffrey P. Reiss

Bibliographic record

VenueEvolutionary Psychology · 2006
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsJokeHumor researchPsychologyLaughterCognitionEvolutionary psychologyBonoboCognitive scienceRelevance (law)EthologyCognitive psychologySocial psychologyEvolutionary biologyBiologyNeuroscienceLinguisticsPhilosophyEcology

Abstract

fetched live from OpenAlex

Humor is a complex cognitive function which often leads to laughter. Contemporary humor theorists have begun to formulate hypotheses outlining the possible innate cognitive structures underlying humor. Humor's conspicuous presence in the behavioral repertoire of humankind invites adaptive explanations. This article explores the possible adaptive features of humor and ponders its evolutionary path through hominid history. Current humor theories and previous evolutionary ideas on humor are reviewed. In addition, scientific fields germane to the evolutionary study of humor are examined: animal models, genetics, children's humor, humor in pathological conditions, neurobiology, humor in traditional societies and cognitive archeology. Candidate selection pressures and associated evolutionary mechanisms are considered. The authors conclude that several evolutionary-related topics such as the origins of language, cognition underlying spiritual feelings, hominid group size, and primate teasing could have special relevance to the origins of humor.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.333
Teacher spread0.287 · 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 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

Citations173
Published2006
Admission routes1
Has abstractyes

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