Competitiveness of organic arable crop production- comparison between Croatia and Canada
Bibliographic record
Abstract
The combination of customer awareness of food quality and man-made environmental problems is leading to greater acceptance of organic production worldwide. Organic farming occupies an important place in recent EU policies, particularly the Green Deal and the Farm to Fork Strategy. The EU plans to increase organic production to 25% of utilized agricultural land by 2030. Despite the generous support planned for organic farming, farmers' willingness to convert depends on the business results and market potential of organic farming. In comparison with mainstream conventional agriculture, organic farming has several advantages such as the production of healthy food, environmental protection, increasing biodiversity and animal welfare. However, like any other business, organic production is necessary to be profitable and to be commercially competitive. The thesis aims to compare the competitiveness of wheat, corn, barley and hemp in Croatia and Canada. The objective of the study is to assess the economic viability and risk of organic grain production, examine the relationship between production cost structures and farm performance, examine efficiency, and specifically address economies of scale in competitiveness. This study provides estimates of Domestic Resource Cost for wheat, barley, corn and hemp in Canada and Croatia, thereby evaluating competitiveness and comparative advantage of these agricultural commodities. According to the DRC methodology, the findings indicate that organic wheat, maize, and hemp production demonstrate competitiveness in both countries. However, in the case of barley, production does not possess economic viability. This research holds significance for researchers who are interested in learning more about the profitability structure of organic agriculture. Moreover, policymakers seeking to assess the necessity of subsidies for organic farmers, as well as farmers considering the cultivation of organic food, may find this study to be invaluable.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".