Review of <i> Agricultural Policy, Agribusiness, and Rent-Seeking Behavior</i> By Andrew Schmitz, Hartley Furtan, and Katherine Baylis
Bibliographic record
Abstract
This excellent text is suitable for senior undergraduate students and graduate students in agricultural economics and agribusiness. Its underlying premise is that the formation of agricultural policy is driven by rent-seeking behavior and that agribusiness is an important participant in the policy process. The book goes on to contrast agricultural policies in Canada and the United States through this rent-seeking lens. Although its title's emphasis on rent-seeking and agribusiness is somewhat misleading, the volume offers an excellent economic analysis of agricultural policy. Rent-seeking is a dominant theme but certainly not the book's focus, unless policy and rent-seeking are simply seen as tautologous. Agribusiness receives little attention other than being identified as a major player in rent-seeking and lobbying activity. Despite this weakness, this is one of best and most comprehensive texts on the economics of agricultural policy currently available.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".