SOUTHERN JOURNAL OF AGRICULTURAL ECONOMICS DECEMBER, 1983 IRREVERSIBLE IMPORT SHARES FOR FROZEN CONCENTRATED ORANGE JUICE IN CANADA
Bibliographic record
Abstract
Canada is the most important U.S. export market for lagged dependent variables (Houthaker and Taylor), frozen concentrated orange juice, accounting for over segmented independent variables (Goodwin et al.; 8 million gallons of exports each of the past 9 years. Tweeten and Quance; Houck), and a variety of other Brazil and the U.S. are the dominant suppliers of or- techniques, including time-varying parameters (Ward ange juice in Canada. Prior to 1975, the U.S. held more and Tilley). Each of these approaches has been used than 60 percent of the Canadian market. Brazil's share for a variety of reasons. The reasons for hypothesizing of the market has grown dramatically in the past ten irreversibility can generally be classified as: (1) psy-years, capturing more than a 50 percent share in 1978 chological, (2) technological, and (3) institutional (see Table 1). Brazil's success in gaining a dominant (Nerlove, p. 1). market share can be partially traced to freezes in Flor- In the Canadian orange juice market, technological ida in 1977, 1981, and 1982 that severely curtailed U.S. factors are a major source of irreversibility because of production of oranges for processing. As a result of the form in which the product is imported from the U.S. these shocks and concern about the decrease in the U.S. and Brazil. market share, competitive advertising strategies have Nearly 90 percent of U.S. exports to Canada are al-been adopted by the Florida Department of Citrus. In ready packaged, with the rest delivered as high-den-
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.037 | 0.002 |
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".