Primary Data: Cases from the Winery Industry in Canada, France, and Chile
Bibliographic record
Abstract
In order to build theory on the role of family firms in investing patient capital for long-term sustainability strategies, we supplemented the literature review with empirical case studies to generate a thicker description of the phenomenon and to embed the arguments in practice. In subsequent chapters of this monograph, discussions and theory development is illustrated with examples drawn from these case studies. In order to generate an understanding of the core phenomenon, the cases were selected to allow comparison between family and non-family controlled firms operating in similar institutional, legal, political, and societal environments. To control for exogenous influences, the winery industry was chosen due to similararity in products, services, activities, supply chains, markets, industry standards, and similar institutional contexts across regions in Canada, France, and Chile represented in both New World and Old World wineries. The winery industry exhibits a range of governance structures from corporate wineries to multi-generational firms to first generation and lifestyle firms, allowing comparisons on the core concepts examined.
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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 | 0.007 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".