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Record W609456694

Warhol Goes Social: creativity in the tech age

2013· article· en· W609456694 on OpenAlexaboutno aff
Mitch Goodwin, Laurie Frick, Christiaan Welzel, David Albert Jones

Bibliographic record

VenueResearchOnline at James Cook University (James Cook University) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityBoomBeautySocial mediaSession (web analytics)Visual artsMedia studiesSociologyAestheticsArtAdvertisingPsychologyEngineeringPolitical scienceSocial psychologyLawBusiness
DOInot available

Abstract

fetched live from OpenAlex

Mitch Goodwin was invited to speak on the panel session, Warhol Goes Social at the SXSW Interactive conference component of the 2013 SXSW Festival in Austin Texas. The panel was composed of Goodwin, artist Laurie Fricke, Associate Creative Director at Critical Mass Christiaan Welzel and the panel was moderated by David Jones, VP of Social Media at Critical Mass (Canada). Today, everyone is a "Creative." With the boom of visually-based social platforms like Instagram and Pinterest, technology has leveled the playing field. Does this really change how we define art and creativity? Artistic purists believe these tools cheapen the creative output with seventeen standard filters available to every untrained eye. But in true entrepreneurial spirit, those apps encourage a more democrative view of creativity, allowing user to share their inspiration with their friends and create beauty where it previously would have been impossible. Is there a difference between high-brow and low-brow art in relation to what social media enables everyone to create?

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.049
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.008
Scholarly communication0.0180.014
Open science0.0010.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0490.009

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 head0.059
GPT teacher head0.291
Teacher spread0.232 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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