Entrepreneuriat, formalisation de la gouvernance et modes de croissance en agriculture : Étude de sept cas de grandes exploitations agricoles au Québec
Bibliographic record
Abstract
The farmer as a business leader is generally recognized as the main person responsible for the conduct of his business and therefore the strategies put in place to operationalize the growth. It has been shown, however, that farmers as well as managers of large companies are supervised, influenced, but also constrained in their strategic choices by a system of governance made up of various stakeholders and various mechanisms. In the specific context of the Quebec agricultural sector, where the potential for development is significant, the objective of this article is to better understand the specificities of the owner-manager and the governance system of particular farming models that develop and their links to the growth trajectories of the farms concerned. The results show, with the realization of 7 case studies, the presence of an agri- entrepreneur (with the characteristics of ambition of growth, team management and social network, risk-taking, opportunity and innovation), a strong involvement of external actors as partners of the manager as well as a formalization of the governance and organization of the company in these developing exploitations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".