From farms to tables: Quantifying the effect of emissions pricing on Canadian food prices
Bibliographic record
Abstract
Abstract We examine the effect of emissions pricing on the cost of Canadian food. We describe emissions pricing policies relevant to the agriculture and food sectors and the differing design details of various provincial systems and the federal Greenhouse Gas Pollution Pricing Act . To quantify the potential effect of such policies, we use a detailed input‐output model of Canada's economy to estimate both the direct and indirect cost increases across sectors. We also explore how exemptions and policy design can mitigate what would otherwise be larger effects. In particular, imported inputs, generous exemptions for most direct emissions in primary agriculture, and special provisions for large industrial emitters all dampen the effect. Overall, we find that emissions pricing at $80 per tonne could potentially increase the cost of domestically produced food by approximately 0.8% on average. Combined with imported food that is not directly affected by emissions pricing, we find an average effect of approximately 0.5%. While we abstract from general equilibrium responses, our analysis suggests emissions pricing in Canada has only a modest effect on food costs.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".