Sustainable Innovation in the Canadian Agrifood Sector: Past, Present & Future
Bibliographic record
Abstract
In order to remain globally competitive with sustainable innovations in agri-food, both the public and private sectors in Canada must increase investment and in the industry. Studies reveal that both sectors’ support for agri-food innovation has declined in recent years. To spur innovation and growth public funding should revert to previous levels, ideally reaching 0.10 per cent of GDP. Incentives such as tax relief, matching funds and enhanced protection of intellectual property rights could spur increased levels of private sector investment in innovation. In the past 50 years, innovation in agriculture has brought tremendous benefits to producers, processors and consumers. Successful innovations include genetically modified crops, large-scale cattle feeding operations and the adoption of no-till farming, which has reduced the traditional practice of summerfallowing fields. Still, with the demand for a secure global food supply and growing concerns about the environmental impacts of large-scale farming, the need for sustainable innovation in the agri-food sector is pressing. This paper offers three recommendations for policy-makers. First, public funding for agricultural research and development should be increased to prior levels. Next, the private sector needs more favourable conditions to foster investment in the agri-food industry. Last, if intellectual property rights are strengthened, innovating firms will be reassured that they can capture the economic benefits innovation creates.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".