Milked and Feathered: The Regressive Welfare Effects of Canada’s Supply Management Regime: Reply
Bibliographic record
Abstract
A comment by Doyon, Bergeron, and Tamini (2018) criticizes the approach and the results of a study by Cardwell, Lawley, and Xiang (2015) that quantifies the distributional effects that Canada’s supply management regime imposes on consumers. In this reply, we show that the main empirical result of Cardwell et al.—the degree of regressive distributional effects—is robust to alternative modelling choices and to alternative counterfactual price scenarios. We present new food price comparisons between Canada and the United States, showing that significant price premiums for supply-managed products persist under different exchange rates. Contrary to the results in Doyon et al., we find no evidence of systematic price premiums for non-supply-managed food products. Our new price comparisons highlight the shortcomings in the price comparisons in Doyon et al. and corroborate the results in Cardwell et al. Finally, we reject suggestions by Doyon et al. that our results are affected by research bias.
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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 | 0.011 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.040 | 0.046 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".