Cattle/Beef Subsector's Structure and Competition under Free Trade." Pp
Bibliographic record
Abstract
This paper discusses the cattle and beef industries of Canada, Mexico, and the United States with a look at their structure and competitiveness in a future free trade environment. Some might argue, with r ason, that these industries already operate in just such a world. While that may be true these industries are going through rapid structural change that makes a look at the next 20 years very interesting indeed. The last 5 years provides an excellent blueprint for structural change as a source of trade disputes. The cyclical nature of the cattle industry led to a sharp decline in cattle prices in 1994 and culminated with extremely low prices in 1996. Drought in the Southwest and Mexico exacerbated the low prices as more cows went to market. Corresponding with low prices were increased numbers of calves and fed cattle coming to the US from Mexico and Canada. The number of cattle coming to the US expanded rapidly in the mid-1980s to more than one million head coming from Mexico and Canada each. The visible shipment of those cattle to the US led to several ITC suits and other trade disputes. These trade disputes are a direct result of structural changes in the cattle/beef sector.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.082 | 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".