The governance of agriculture: Global programs of development and agricultural biotechnology.
Bibliographic record
Abstract
In the name of progress and growth, the apparatus of development has formed a mode of global governance. This apparatus consists of development discourses and institutions and attempts to govern agriculture, pointing to the current effort underway to liberalize agriculture on a global scale. Farmers of the developing world are now subject to a regime of control that includes international institutions of governance, nation-state governments and multinational corporations. By examining the role of specialized agencies of the United Nations, specifically the FAO and UNESCO in the governance of agricultural practices, I focus on the implementation and management of agricultural biotechnology and genetic engineering in the farming practices of the rural peoples in the developing world. I specifically examine the extent to which the concept of expert knowledge has influenced the incorporation and development of agricultural biotechnologies into these farming practices. Based on my analysis, I illustrate how the FAD and UNESCO, through their reliance upon professional forms of expert knowledge, facilitate the global management of agricultural practices.Dept. of Sociology and Anthropology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .G74. Source: Masters Abstracts International, Volume: 44-03, page: 1250. Thesis (M.A.)--University of Windsor (Canada), 2005.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".