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Record W6893663242 · doi:10.5281/zenodo.4609374

Looking Seriously At Improvisational Comedians: An Existential-Phenomenological Analysis

2018· article· en· W6893663242 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsImprovisationCraftComedyLeverage (statistics)StressorAnxietyQualitative researchPerception

Abstract

fetched live from OpenAlex

For all their ability to make us laugh, many comedians report severe struggles with mental health. Even so, this reality does not deter a growing number of improvisational (improv) comedians from endorsing applications of their craft in wellbeing-oriented workshops for the public, which claim to leverage the beneficial side effects of learning improv comedy to help with a growing list of psychological ailments like social anxiety and autism. This existential-phenomenological study explored the complex dynamics of wellbeing among eight professional improvisers (five men and three women) to illuminate the psychological vulnerabilities and resiliencies of this unique subset of the comedy community. Qualitative analysis yielded six common themes that conveyed the beneficial personal "by-products" of doing improv, which included the opportunity for adults to play, the joy of collaborative relationships, increased comfort with risk, improved confidence, a focus on positivity, and a revitalizing effect on emotional health, self-image, and sense of purpose. Stressors unique to the business aspect of improv, but not improv itself, were also revealed. Results provide valuable insights both for improvisers and those interested in the application of improv in clinical settings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.709
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0970.017

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 head0.060
GPT teacher head0.321
Teacher spread0.261 · 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; both teacher heads agree on what is shown here.

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
Published2018
Admission routes1
Has abstractyes

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