How Did Canada‘s Increasing Lentil Production Affect Turkey? Is There A Possible Win-Win Situation for Both Countries?
Bibliographic record
Abstract
Competition is fierce in the world markets of agricultural products. It is especially harder for developing countries to compete with the wealthier industrialized countries. Canada entered in the lentil production mainly for export purposes in the early 1990s and exports nearly all of its lentil products every year. As Canada has become the dominant power in lentil trade, Turkey‘s lentil production has declined notably. In the study, Turkey‘s adaptation to this trend is investigated. Based on the results, it is concluded that Turkey‘s market share has not changed in its traditional markets and its export has risen both in quantity and value. For instance, Turkey‘s lentil export has increased from 127 Thousand tons in 1997 to 178 Thousand in 2013. This is achieved through partnerships between Canadian and Turkish entrepreneurs. Furthermore, lentil producers in Turkey have shifted to alternative crops, which yields higher income.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".