Ten percent organic within 15 years: Policy and program initiatives to advance organic food and farming in Ontario, Canada
Bibliographic record
Abstract
Abstract With growth in retail sales estimated by industry at 15–25% yr −1 , organic food represents the only significant growth sector in Canada's food system. This reality, in combination with mounting evidence that substantial environmental and economic benefits can arise from organic farming adoption, suggests that organic sector development should be a priority for governments. However, organic food remains a marginal component of Canadian agricultural and trade policy. This study was designed to examine the opportunities and costs to the province of Ontario of strategic investment in the expansion of the organic sector. Drawing on existing literature and Ontario land use and production data, the study used an iterative process to identify how the province could reach a target of 10% of Ontario's cropped acres in organic production within 15 years, from the current level of about 1%. We concluded that after 15 years 5343 organic farmers would be producing organically in all major commodities, including 4254 converting farmers entering the organic sector and 600 new entrants to farming. The 489 organic farms reported in 2004 would be included in this total of 5343 because we assume that they all make modest additions over this time period to their existing operations. Organic production would occur on about 367,000 ha of land, and some 1.4 million animals would be reared organically. After 15 years, these farmers would reduce fertilizer applications by about 43 million kg (saving $18.4 million yr −1 ), pesticide applications by about 296,000 kg active ingredient (saving $9.1 million yr −1 ), and 7079 kg of growth-promoting antibiotics/medications consumed in animal feed. This 30-point program would require new investments by the provincial government of about $51 million over 15 years. Phase I (first 5 years) costs would total $7.1 million and Phase II (following 10 years) costs $43.9 million. Net program costs would be significantly lower since farmers would have directly saved on inputs and received premium organic prices for most of their goods sold, thereby reducing government costs related to supporting farm finances. Additionally, this program would contribute significantly to reducing the externalized costs of current approaches to agriculture, conservatively estimated at $145 million annually or $2.18 billion over the 15-year life of the program. Not all those costs would be saved within 15 years, but this exceedingly modest investment in organic production, representing only 2.3% of these externalized costs, would generate savings in externalized costs far beyond this one-time investment. Implementation of this plan would allow domestic producers to capture 51% of Ontario's organic consumption, up from the currently low-range estimate of 15%. Organic foods would represent 1.9% of the total food retail market after 5 years and 5.3% of the total market after 15 years.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".