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Record W3007363789

"It's got to be dirty": Komodifikace vzpomínání na případu souboru Prague Burlesque

2017· dissertation· cs· W3007363789 on OpenAlexaboutno aff
Oldřich Poděbradský

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2017
Typedissertation
Languagecs
FieldSocial Sciences
TopicLanguage and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsBurlesqueArtArt history
DOInot available

Abstract

fetched live from OpenAlex

This thesis focuses on the commodification of remembering in the case of the Prague Burlesque group. Burlesque or neo-burlesque as an entertainment genre is not as well known in the Czech context as it is in Western Europe, USA or Canada. However, after ten years of activities of the Prague Burlesque, this genre has been receiving more and more recognition in the entertainment market. In this thesis I focus on the perception of burlesque and remembering on the "golden age" as percieved by the members of the Prague Burlesque group as well as the audience of the shows, and how this remembering is commodified in the field of marketing, ether in relation to the regular Prague Burlesque Show or the annual Prague Burlesque Festival. This thesis combines theoretical concepts relating to simulacra (Baudrillard, Mac Cannel), collective memory (Halbwachs, Erll) and commodification of retro and nostalgia after the World War II (Grainge, Moore) with my field research, which took place from 2015 to 2017.

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)0.001
metaresearch head score (Gemma)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0060.004
Open science0.0000.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.014
GPT teacher head0.295
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

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

Citations0
Published2017
Admission routes1
Has abstractyes

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