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Record W4206796363 · doi:10.1177/0308518x211063216

Multiple entrepreneurial ecosystems? Worker cooperative development in Toronto and Montréal

2022· article· en· W4206796363 on OpenAlexaffabout
Jason S. Spicer, Michelle Zhong

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSocial connectednessConstruct (python library)BusinessEcosystemMarketingIndustrial organizationEcologyComputer sciencePsychologySocial psychologyBiology

Abstract

fetched live from OpenAlex

The emergence in practice of worker cooperative ecosystems, which draws on the entrepreneurial ecosystems (EEs) concept, has been largely ignored in academic research. Contrasting worker cooperative development efforts in Toronto with Montréal, we affirm there are multiple and multiscalar EEs in each region, including both a dominant capitalist and a worker cooperative EE. Productive enterprises like worker cooperatives, operating with a different logic than investor-owned firms, not only construct their own EE, but the relational connectedness of the worker cooperative EE to other EEs also plays a role in outcomes. Worker cooperatives have been less successful in navigating these dynamics in Toronto than in Montréal. Future research might seek to more fully specify the relational and multiscalar configuration of regions’ multiple EEs.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.006
Scholarly communication0.0050.002
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.009
GPT teacher head0.174
Teacher spread0.165 · 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

Citations27
Published2022
Admission routes2
Has abstractyes

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