Beef and Plant Protein: Stronger Together
Bibliographic record
Abstract
Governments should look at the beef and plant protein industries as one protein market with multiple commodities, say participants at a protein industry roundtable held recently at the University of Calgary. The synergies between the sectors can be used to present a strong, sustainable, trusted brand for the Canadian protein market, both domestically and internationally, driving investment for infrastructure and innovation that could improve Canada’s global position for protein production and export. The government should consider developing policies and regulations that can help facilitate such a collaboration. The roundtable of protein industry stakeholders was hosted by the Simpson Centre for Food and Agricultural Policy, an applied research policy institute at the University of Calgary’s School of Public Policy, whose goal is to mobilize research for better policy- making and decision-making to realize a more sustainable agricultural industry. Discussing the challenges and opportunities for the beef and plant protein industries, the participants agreed that working together would offer many benefits. By presenting a united front, the protein industry has a better chance of lobbying governments for mutually beneficial changes, attracting more investments for infrastructure to increase efficiency and reliability, educating consumers on the synergies between the industries and branding Canadian protein as a sustainable, reliable and abundant market. Branding is a key factor in the protein market — consumers, investors and governments need to see the plant and beef protein sectors as partners, not competitors. They need factual information from the industry — rather than be influenced by misperceptions spread by social and mass media — to be satisfied with the agri- products being produced and with the methods of production. The roundtable participants cited one example of a synergy with benefits on multiple levels — using the by-product from plant protein production to feed cattle. This helps with sustainability in both the beef and plant protein industries, particularly with current global supply chain issues brought on by drought, conflict and other factors. It is also environmentally friendly and demonstrates that the industries can work together for each other’s benefit. This type of innovative synergy would also improve consumers’ perceptions of the beef and plant protein industries, besides driving investment and expansion. Governments need to consider the opportunities that a unified protein market can provide for Canada. A strong, sustainable protein market has the potential for exponential growth, particularly with ongoing global supply chain issues and food security concerns.
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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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.018 |
| Scholarly communication | 0.016 | 0.022 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.048 | 0.006 |
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".