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Record W3135384566 · doi:10.1177/0950422221999222

The Music Den: A framework for entrepreneurship education in a university start-up incubator

2021· article· en· W3135384566 on OpenAlexaffabout
Cormac McGee, Noah Schwartz, Steven Paul Ehrlick

Bibliographic record

VenueIndustry and Higher Education · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsIncubatorEntrepreneurshipMentorshipEntrepreneurship educationCurriculumSociologyPedagogyMusic educationBusinessMedical education

Abstract

fetched live from OpenAlex

This account of practice details an ongoing approach to entrepreneurship education currently being implemented at a large urban university in Toronto, Canada. The Music Den is an entrepreneurship incubator focusing on the music industry that collaborates with start-up businesses, music projects, industry, local communities and postsecondary students. The incubator deploys a pedagogical model that promotes self-direction and mentorship by way of adaptable curricular programming. The program design utilizes social constructivist principles to deliver a novel entrepreneurship education curriculum.

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)0.006
metaresearch head score (Gemma)0.003
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: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0090.019
Scholarly communication0.0150.009
Open science0.0030.008
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.033
GPT teacher head0.271
Teacher spread0.238 · 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
GenreMethods

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

Citations11
Published2021
Admission routes2
Has abstractyes

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