Implications of carbon pricing on food affordability and agri-food sector in Canada: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Food affordability is a critical issue in Western countries. • Carbon taxes influence broader economic dynamics. • Limited research in Canada on the effects of carbon taxes on food prices. • As of 2020, over 30 economies worldwide have implemented carbon taxes. • Carbon taxes reduce disposable income and raise food prices. This review delves into the effects of carbon pricing policies on food affordability and the performance of the agri-food sector, with a specific focus on Canada. Against the backdrop of the widespread adoption of carbon pricing as a crucial tool in reducing greenhouse gas (GHG) emissions, the discussion acknowledges potential economic repercussions, particularly for lower-income households. Findings reveal that the implementation of a mandated carbon tax across all provinces in Canada by 2019 led to reduced GHG emissions and an increase in food prices. In addition, this review positions Canada within the global context by examining actions taken by other countries and their impacts. Crucial research gaps are also identified, ultimately serving as a guide for future studies and policy formulation aimed at balancing the necessity of carbon tax implementation with considerations of food affordability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it