Integrated approach to accounting in the context of sustainable development and circular economy
Bibliographic record
Abstract
In today’s environment, ensuring sustainable development is one of the long-term goals of any state, and therefore consideration of new approaches and concepts remains relevant. The purpose of this study was to investigate approaches to accounting in the context of the circular economy. The study assessed some main approaches to financial reporting based on the principles of sustainable development and the circular economy, and conducted a comparative analysis of the similarities and differences. Conclusions were drawn regarding the role of existing standards in the activities of enterprises in the context of achieving sustainable development goals. The large number of existing international and national standards results in the absence of a single global approach that could meet the needs of all market participants. In addition, each approach focuses on a specific component of non-financial reporting disclosures, and therefore is more or less effective in different situations. An analysis of accounting approaches in countries such as Japan, Germany, Finland, the United States, Canada, Brazil, and Ukraine was conducted. It was found that in these countries, the general approaches are similar and based on international standards, while in some countries local laws may be applied, which form more specific reporting principles. The findings of the study highlighted the importance of a unified global approach to reporting that can meet the needs of the market. The practical value of the study lies in the possibility of using the results to develop public policy and corporate strategies in the field of sustainable development
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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".