5.0 Implications for Economic Development in Rural Ontario
Bibliographic record
Abstract
Collective entrepreneurship, at first glance, appears to be a new term that combines business risk and capital investment with the social values of collective action. Certainly, this is an appealling proposition. A second look at the term begs the question: Is this an oxymoron? Can we use “collective ” and “entrepreneur ” together? From a conventional perspective, one that equates entrepreneurship with a highly successful, self-employed individual, the two terms may seem related like lead is to balloons. In this regard, collective entrepreneurship may not withstand scrutiny. As many buzz words, it may simply slip from use. Nevertheless, this paper seeks to explore the multiple facets of the term and its possible application in rural economic development. The starting point of this paper is a review of entrepreneurship, sans collective. A brief look at the importance of entrepreneurship highlights its significant role within economic development. This helps to establish a context within which to explore the many dimensions of entrepreneurship. Another perspective of entrepreneurship, this time within the history of economic thought, reveals the origins of the characteristics commonly associated with
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".