Bibliographic record
Abstract
The purpose of this paper is to discuss on distortion effects of State Trade Enterprises "STE" on international markets of agricultural commodities. Particularly, it is the STE which has been operating under the single desk status in either domestic marketing or export marketing that matters in this arguments. The objective function of STE activities is to maximize total revenue of producers while the objective function of private trade enterprises is to maximize their own profits. Last December, WTO had the conference for extending the trade liberalization measures which had been agreed in GATT Uruguay Round. However, it had failed to reach to the agreement of further liberalization due to objections by the LDC and NGO against the USA proposals. Since then, WTO has tried to have another chance for conference to discuss about liberalization again. USA has proposed the issues of STE as the agenda for the next conference. As for the exporting countries, most of Cairns group have STEs. Each member countries of Cairns group have not always shown the same attitude for this arguments. For example, Australia and New Zealand have privatized several STEs such as Australian Wheat Board or New Zealand Dairy Board etc. However, Canada has not privatized any STEs such as Canadian Dairy Committee etc. As for the importing countries, Japan has STEs such as Food Agency, Agriculture & Livestock Industry Corporation and Japan Tabaco Incorporated. China has both exporting STE and importing STE. Since China has been adopting the Planning Economy system, its trading firms had been owned by the government originally. However, China has been trying to separate the management aspects as the self owned organizations from the administration side of the trading firms. As for the distortion effects of STEs, their "pooling systems" are argued. Most STEs have adopted the following 3 types of pooling systems. i.e. (i) pooling of revenues in domestic marketing and export marketing, (ii) pooling of marketing revenues in profitable export markets and nonprofitable export markets and (iii) pooling of marketing revenues of high grade commodities and low grade commodities. In this paper, 3 economic models are introduced to measure the market distortion effects of the STEs and discussed on their comparative validity in each of the pooling systems.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".