Bibliographic record
Abstract
The circular economy requests a feedback flow of “resource-production-reborn resource” for the economic activity, and it sparkplugs decrease, reuse and recycle. Our country should use experiences of the western country for reference, ensure development of circular economy by legislation, and accelerate the pullulating of circular economy and sustainable development of economy by perfecting the three-simultaneity system, budget and statistics system, financial subsidy system, government procurement system, taxation regulation system, producer responsibility system, and clean production system etc. Keywords: circular economy, the principle of 3R, clean production, circular-economy law Resume L’economie cyclique demande une procedure retroactive comprenant « ressources-produits-ressources renouvelees » pour organiser l’activite economique, preconise la reduction, le remploi et le recyclage. Notre pays doit , en s’inspirant des experiences avancees des pays occidentaux, assurer la construction economique par la legislation, promouvoir l’economie cyclique et le developpement durable de l’economie en perfectionnant le regime de « trois en meme temps », le systeme de budget et de statistique, le systeme des allocations financieres, le systeme d’achats du gouvernement, le systeme de regulation fiscale, le systeme de responsabilite des producteurs, le systeme de production sanitaire, etc. Mots-cles: economie cyclique, principe « 3R », production sanitaire, loi de l’economie cyclique 摘 要 循環經濟要求將經濟活動組織成一個“資源—產品—再生資源”的反饋式流程，倡導減量化、再利用和再循環。我國應借鑒西方先進國家經驗，以立法保障循環經濟的建設，並通過完善三同時制度、預算及統計制度、財政補貼制度、政府採購制度、稅收調節制度、生產者責任制度、清潔生產制度等，促進循環經濟的成長和經濟的可持續發展。 關鍵詞：循環經濟； 3R原則；清潔生產；循環經濟法
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.018 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.011 | 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".