Canadian dairy regulations as a driver of foreign direct investment: the case of Saputo
Bibliographic record
Abstract
Across North America dairy processors are facing financial difficulties, yet a Canadian processor continues to grow through acquisitions of its competitors. This company, Saputo, grew up in a highly regulated marketplace where input raw milk supplies are restricted, input prices are inflated and imports of final product are restricted. This study asks if the Canadian system of dairy supply management prodded and assisted Saputo into making acquisitions at home and abroad. An empirical model estimates the probability of Saputo making acquisitions as a function of factors influenced by supply management and control variables accounting for Saputo’s financial performance. The results indicate that cash flows, which may be increased by regulatory rents, and a measure of restrictiveness of the Canadian milk supply, both are statistically significant positive determinants of the probability that Saputo will make an acquisition. On average over the estimation period removing the Canadian supply managed regime would reduce the probability of acquisitions by 7%. The implication is that the Canadian system is losing investment and employment opportunities by retaining its restrictive regulatory system.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".