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Record W4393068222 · doi:10.5771/9781442230095

Case Studies in Cultural Entrepreneurship

2015· book· en· W4393068222 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueRowman & Littlefield Publishers eBooks · 2015
Typebook
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsDowntownThe artsEntrepreneurshipVariety (cybernetics)InstitutionArts administrationManagementPolitical sciencePublic relationsSociologyGeographyArchaeologySocial science

Abstract

fetched live from OpenAlex

This book of five case studies demonstrates the critical role entrepreneurs and entrepreneurial thinking play in reinventing cultural organizations to make them relevant and sustainable for the twenty-first century and beyond. Through the twin lenses of cultural entrepreneurship and organizational change, these readable and inspirational cases offer an in-depth analysis of how a variety of cultural organizations—small and large; local, regional and national; museums and arts organizations—have found opportunities in complex situations to create new identities and missions and, in doing so, have revitalized their organizations and in many cases, surrounding communities. Cases include: The Strong: how a museum in Rochester, New York, forged an entirely new national identity as The National Museum of Play. National Mississippi River Museum and Aquarium: how the Mississippi River Museum developed and nurtured a network of partnerships to create a new regional identity and, in doing so, revitalized the waterfront area of Dubuque, Iowa. Montreal Center for History: using oral history and community collaborations to dramatically build its audiences throughout the city. Proctors: how an arts organization revitalized downtown Schenectady, New York Weeksville: how an institution in one of the poorest neighborhoods in New York City found a niche that provided vital services to its constituency.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.198
GPT teacher head0.356
Teacher spread0.158 · 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