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The Hermeneutics of Poetry Slam: Play, Festival and Symbol

2015· article· en· W4400610512 on OpenAlexaffvenue
W. John Williamson

Bibliographic record

VenueJournal of Applied Hermeneutics · 2015
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPoetrySymbol (formal)Event (particle physics)HermeneuticsExperiential learningLiteratureAestheticsHistorySociologyArtEpistemologyPhilosophyLinguisticsPedagogy

Abstract

fetched live from OpenAlex

In this paper, I discuss Poetry Slam events as hermeneutic encounters. Gadamer’s analysis of play, festival, and symbol form the theoretical basis of the discussion. Exemplary data include my research into aspects of the history and ritual of Slam as well as my experiential data as a spectator, coach of a Poetry Slam team of adolescents who compete in a provincial tournament for young poets, and as a Slam performer. I contend that, despite Slam’s occasional “silliness,” occasional problems of quality and fair play, and the insistence of many academics that it is not a worthwhile celebration of literature, Poetry Slam has the potential to create meaningful connections between diverse communities and tarry over language as a hermeneutic event. I note that, in an era where text is generated with increasing rapidity while our abilities to appreciate language as an event or as a means of connecting with each other are undermined, Poetry Slams might be the kind of festival we need to seek relief from these trends.

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)0.005
metaresearch head score (Gemma)0.009
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 score0.010
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.051
Scholarly communication0.0100.008
Open science0.0010.007
Research integrity0.0020.004
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 head0.041
GPT teacher head0.326
Teacher spread0.285 · 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
Published2015
Admission routes2
Has abstractyes

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