Over 6 billion liters of Canadian milk wasted since 2012
Bibliographic record
Abstract
Canada's dairy supply management system provides milk year-round but unnecessarily disposes of overproduction. A lack of transparent data on discarded milk means that the scale of this issue is unknown. This hinders actions to mitigate the potentially large environmental, economic and nutritional costs of avoidable, on-farm milk waste. Here we estimate the volume of surplus milk discarded on farms using a material flow analysis approach, and assess the related environmental and nutritional costs. By our estimates, over 6.8 billion liters of raw milk vanished from Canadian dairy farms since 2012 (totaling a value of $14.9 billion CAD). We calculate this is equivalent to 8.4 million tonnes of CO 2 emissions and enough milk for 4.2 million people (11 % of the Canadian population) annually. We suggest increasing transparency on the volume overproduction, reducing incentives for farmers to overproduce, and updating quotas to reflect shifting dietary needs as actions to align the Canadian dairy sector with broader food-system sustainability objectives.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".