Canadian Agricultural Innovation and Regulation Network (CAIRN) CAIRN Commissioned Paper On the Relationship between Regional Trade Agreements and Agricultural Technology and Productivity
Bibliographic record
Abstract
Abstract: The implementation of a Regional Trade Agreement (RTA) is normally accompanied with a rise in market competition levels, in domestic agricultural markets through increases in imports and in foreign agricultural markets through increases in exports. These effects are expected to induce adjustments in agricultural technology and productivity in the importing and exporting countries. This paper analyzes the implications of these adjustments in the context of Viner’s (The Customs Union Issue. Carnegie Endowment for International Peace: New York, NY, 1950) conventional partial equilibrium framework with perfectly elastic foreign supply schedules faced by the importing member country. It also examines these implications in the context of Pomfret’s (Review of World Economics, 122(3): 439–465, 1986) extended partial equilibrium framework depicting upward-sloping foreign supply schedules for the importing member country. The analysis underscores important changes and redistributions through the RTA’s initial benefits and losses, following the RTA-induced adjustments in agricultural technology and productivity. Some analytical considerations are also discussed in the context of vertical agricultural markets.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.004 |
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".