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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 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

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

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