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Record W4390886211 · doi:10.1080/00020184.2023.2299222

Politics, Jokes and Power in Africa: The View From Stand-Up Comedy

2023· article· en· W4390886211 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAfrican Studies · 2023
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComedyPoliticsDramaPower (physics)LaughterPatienceImpeachmentSociologyMedia studiesGender studiesHistoryPolitical scienceLawLiteratureArtPsychologySocial psychology

Abstract

fetched live from OpenAlex

The history of stand-up comedy in Africa has often been tied to developments in popular culture, language, and performance. In this article, I take a different perspective by identifying the interactivities of politics and comedy, and how the actions, endorsements, and even censure of national leaders across different nations buoyed up stand-up performances on the continent. With specific examples from different countries, the explications in this paper show how the (in)actions of political leadership in Africa served as fodder for laughter elicitation – in Kenya, with Daniel arap Moi’s capitulation and Mwai Kibaki’s lethargy; in Nigeria, with Olusegun Obasanjo’s comedian-president posture as well as the gaffes of Patience Jonathan; and in South Africa, with Jacob Zuma’s unending drama until his resignation. These situations are equally contrasted with the experiences in Uganda, Egypt and Rwanda, where political censure is variously rife.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.094
GPT teacher head0.375
Teacher spread0.281 · 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