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Record W6887854409 · doi:10.17613/cpmf0-y6k45

Interview with Prof. Dr. Richard Florida: reflections on the creative economy

2019· article· en· W6887854409 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityGeorge (robot)State (computer science)Creative classGovernment (linguistics)Class (philosophy)

Abstract

fetched live from OpenAlex

Richard Florida is one of the world's leading urbanists. He is a researcher and professor, serving as University Professor and Director of Cities at the Martin Prosperity Institute at the University of Toronto, a Distinguished Fellow at New York University's Schack Institute of Real Estate, and a Visiting Fellow at Florida International University. He is a writer and journalist, having penned several global best sellers, including the award winning The Rise of the Creative Class and his most recent book, The New Urban Crisis published in April 2017. He serves as senior editor for The Atlantic, where he co-founded and serves as Editor-at-Large for CityLab. He is an entrepreneur, as founder of the Creative Class Group which works closely with companies and governments worldwide. A 2013 MIT study named him the world's most influential thought leader. And TIME magazine recognized his Twitter feed as one of the 140 most influential in the world. He previously taught at Carnegie Mellon, Ohio State University, and George Mason University, and has been a visiting professor at Harvard and MIT and Visiting Fellow at the Brookings Institution. He earned his Bachelor's degree from Rutgers College and his Ph.D. from Columbia University. For more information about Richard Florida and his work: http://www.creativeclass.com/

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.408
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.103
GPT teacher head0.297
Teacher spread0.194 · 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 teacher head, not a consensus.

Study designNot applicable
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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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