Implications of carbon Taxing policies on the food supply chain in Canada
Bibliographic record
Abstract
• Global food supply chain has been unsteadied since 2020. • Results suggest stress on the wholesale supply chain. • Compounding effect of carbon pricing pushing wholesale prices to rise faster. • Shift in wholesale and industrial prices since introduction of carbon tax. This paper explores the implications of carbon-taxing policies on food supply chain affordability and competitiveness in Canada. Initiated with Alberta’s 2007 carbon levy, Canada’s approach to carbon taxation aims to mitigate greenhouse gas emissions while addressing the economic impacts on the food sector. With the federal carbon price set to rise to CAD $170 per ton by 2030, the study investigates the potential for increased food prices and the challenges to food affordability as well as identify the current gaps in understanding the intricacies of Carbon Taxing Policies on the Food Supply Chain in Canada. Graphic analyses and forecasts were created using data from Statistics Canada and the U.S. Census Bureau. The main findings of the analyses reveal shifts in wholesale and industrial prices since the carbon tax’s implementation. Findings suggest that carbon pricing may be affecting every level of the food supply chain, highlighting the need for further research to understand its full impact on food affordability and security.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".