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Record W4366988203 · doi:10.1080/01596306.2023.2204515

Comic absurdity and profane acts in education

2023· article· en· W4366988203 on OpenAlexaff
Dion Rüsselbæk Hansen, Anne M. Phelan

Bibliographic record

VenueDiscourse Studies in the Cultural Politics of Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Theology and Sovereignty
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAbsurdityComicsComedySociologyHegelianismAestheticsPoliticsAbsurdismOrder (exchange)EpistemologyIronyContradictionMedia studiesLawPhilosophyLiteratureLinguisticsArtPolitical science

Abstract

fetched live from OpenAlex

In this theoretical and provocative paper our aim is to problematize universal ideals, and the closely related belief in educationalization, that frame education today. Inspired by the ethico-political work of Agamben ([2007]. Profanations. New York: Zone Books), and his focus on profane acts of play, and Zupančič's ([2008]. The odd one in: One comedy. Cambridge, MA: The MIT Press) psychoanalytical adaptation of Hegel's ‘concrete universal', we illustrate how universal ideals and beliefs often ‘fail' in comic absurd ways when they are performed in concrete practices. By analyzing different examples, which stem from the research literature, we describe how such ‘failure' looks. We argue that it is important to engage with the comic absurd as doing so can reveal how educators, politicians, and policymakers contribute to the (re)production of failures within the socio-symbolic (educational) order. However, such an engagement may enable us to ‘fail better’ in education if we also allow ourselves to question, challenge, and perhaps change this order by means of profane acts.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.077
Scholarly communication0.0090.011
Open science0.0010.007
Research integrity0.0030.006
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 head0.114
GPT teacher head0.505
Teacher spread0.391 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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