Forecasting the Competitiveness of Major Wheat ExportersAmidst the Russia and Ukraine Crisis
Bibliographic record
Abstract
Major concerns about the food security involving wheat production emerged when the conflict between Russia and Ukraine worsened because both countries were the main suppliers of wheat to 38 countries. This study aims to explore the competitiveness level of wheat production countries and the future exporters that may lead to global wheat production during the Russia-Ukraine crisis. This study analyzed the comparative advantages of the five largest wheat exporters from 2001 to 2021 using the revealed comparative advantage (RCA) and revealed symmetrical comparative advantage (RSCA) indices to examine the current level of wheat export competitiveness of the five major exporters. This study also predicts the three major wheat-producing countries (excluding Russia and Ukraine) using 83-month observations to forecast the autoregressive integrated moving average in the next six months. The findings disclosed that all major wheat countries were strongly competitive, and the forecast unveiled that Australia is capable to lead the wheat producing countries in the next six months. This evaluation was derived from the ARIMA approach’s forecast, demonstrating Australia to be statistically greater than the USA and Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".