Conversion to organic farming and sustainability: a socio-ecological analysis
Bibliographic record
Abstract
This study aims to understand the process of conversion from conventional to organic farming in Canada. Specifically, it looks at what factors have affected this decision and if this production system improved the prospects for sustainability. In order to achieve these objectives this study uses a socio-ecological approach and focuses on organic farmers in Ontario. Besides including a bibliographic review, organic agricultural leaders were surveyed and life story interviews were conducted with producers. The results showed that the decision to become organic is influenced by the type of farmers, their context, and their rationale for conversion. The reasons for converting to organic depended not only on economic factors, but also socio-cultural and institutional parameters. The conversion was associated with a change of values towards protecting the environment and improving farmers’ lifestyles. This model of development doesn't entirely attain sustainability. In order for that to occur, the harmonization of the Canadian organic farming system requires a political solution, which humanizes the complex system of interests for organic producers and shows the potential contribution of organic farming to the achievement of sustainability goals.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".