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Record W4213180817 · doi:10.32920/19158128.v1

A Scientist and a Comedian Walk Into a Bar: Humour’s Role in Science Communication

2022· preprint· en· W4213180817 on OpenAlexaff
Andrea Larney

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsUniversity of GuelphProfessional Engineers Ontario
Fundersnot available
KeywordsScience communicationRealmAction (physics)Public engagementPublic relationsScientific communicationInformation gapSociologyMedia studiesPolitical sciencePsychologyScience educationPedagogyLibrary scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

<p>The art of communicating science to non-scientists (e.g., policy makers, lay-audiences) is the challenge faced by science communicators. Not only is it vital that scientific information leave the realm of academia to be put into action, but the goals of science communication increasingly include public engagement with science. Traditional tactics for public engagement have faced roadblocks in terms of being accessible and actually engaging to a broad audience. Communicators have thus identified that non-traditional techniques, such as adding humour, may make scientific information more accessible. In this MRP, I investigate the use of humour as a creative communication tool to engage the public with science in informal settings. I analyze 34 episodes of a funny science podcast, The Infinite Monkey Cage, to identify how humour is used, and by whom (e.g., scientists, non-scientists). I identify potential roles of common humour types and humour usage styles, as well as the role of each author type. These findings may serve to aid future humorous science communication endeavors, as well as to guide future research.</p><div><br></div>

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.040
GPT teacher head0.311
Teacher spread0.271 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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