The spatial integration of fresh asparagus in select U.S. and Canadian terminal markets
Bibliographic record
Abstract
This thesis investigates the integration of the North American asparagus markets in seven United States terminal markets and Toronto (Canada). In 2008, Ontario exported $4.02 million (US) of asparagus to the U.S., an 880% increase from 2000. Canada has approximately a 1% share of the U.S. fresh asparagus import market; Peru 58% and Mexico the remaining share. The states of Michigan, Washington and California are important suppliers for the traditional U.S. asparagus market. Using a Ravallion Model of market integration, Granger Causality and the Law-of-One-Price hypothesis are tested using weekly prices for week 20-28 for the years 2001-2009. All series, except Toronto, are stationary in levels. Miami's price is fully reflected in Boston, Chicago, Los Angeles, New York and Toronto, while prices from Detroit, Los Angeles and New York are also reflected in Miami. Toronto was determined to be a price taker, although it does Granger cause Detroit's prices.
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".