The political economy of agricultural pest management in Ontario
Bibliographic record
Abstract
This thesis is comprised of a critical assessment of the diffusion/adoption perspective often used to explain the way new techniques come to be utilized in modern agriculture. It is not my intention to refute the theoretical framework of the Diffusion perspective. Instead, I have argued that diffusion studies can be enriched through an examination of the political and economic context into which innovations are introduced. I explore the socio-structural constraints that affect farmers' pest management decisions, through an investigation of the role of agribusiness and the state in promoting particular production techniques favourable to the needs of capitalism. I consider the influence of food processing firms upon the pest management practices used by vegetable growers in southwestern Ontario. I have also analyzed the Research and Development (R&D) objectives directly relevant to pest management in the vegetable industry and the process through which they are determined. Essentially, I argue that the diffusion approach is too shallow given the transformation of agriculture into a capitalist system of production in which the farmer is a seemingly insignificant participant and highly subordinate to agribusiness.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".