Bibliographic record
Abstract
The article analyses the concept of circular economy, its relationship with sustainable development and other areas of economic research. It is emphasised that today the issues of circular economy include waste recycling, renewable energy sources, preserva tion of natural environments, and social aspects. The purpose of the work is to assess the place and the role of the circular economy at the current stage of the agricultural sector development, define the concept of «circular economy paradigm», assess the dynamic processes of soil fertility reproduction from the perspective of circular processes. The authors have formed their own vision of the «circular economy paradigm» concept as a production activity based on minimising the involvement of new natural resources in the production process, while minimising the consumption of non-renewable energy. The coefficient of circular nutrient recovery is offered. This coefficient was tested on the example of Ukraine, Poland and Canada for the period 1992–2020. It was found that the level of circular recovery of nutrients, especially nitrogen, is decreasing in Ukraine. The main factor of this process was a decrease in nitrogen supply due to a manure application reduction. It is concluded that this trend is the main factor in the overall decrease in the value of the circular nutrient recovery coefficient proposed by us. In turn, the decrease in manure supply is due to a significant reduction in the number of livestock. In addition, since 2011, nitrogen supply ha decreased due to its biological fixation, which is asso ciated with gradual changes in the structure of sown areas. There has also been a decline in phosphorus recovery since 2006. In Poland and Canada, nutrient recovery rates have been relatively stable. This raises strategic questions regarding the further development of the entire agricultural sector and the need for a special state policy to change the situation. This policy should be aimed at maintaining biodiversity, developing organic production, the circularity of the entire agricultural sector. The question arises of the influence of the structure of agricultural production on the level of circularity of the economy, in particular the livestock sector. It is also emphasized that the practice of other countries in the development of circular business models in the agricultural sector requires a separate study.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".