GREENING OF DECISION-MAKING PROCEDURES IN THE FIELD OF PUBLIC PROCUREMENT
Bibliographic record
Abstract
The article is devoted to the formation of tasks and development of mechanisms for taking into account environmental criteria in the field of public procurement. A review of program and strategic documents is conducted that address the need to develop the field of public procurement in the context of limiting the impact of factors harmful to health, preserving the quality of natural resources and new approaches in public administration. The article draws attention to the potential of the Aarhus Convention and highlights certain aspects for improving the practice of interaction with the public. It is also noted that the institutionalization of public participation in decision-making was embodied in the discussions of draft regulatory legal acts, projects for the construction of industrial, infrastructure and other facilities. The Law «On Public Procurement» of 2024, which will come into force at the beginning of 2025, is analyzed. The article also provides the EU experience, in particular, the relevant acts on the issue of state (public) procurement to improve the environment are studied. An analysis was carried out, the need for which is dictated by the objectives of the study; it covers foreign practice in regulating and implementing «green» procurement in Sweden, Norway, Denmark, Germany, Canada, the United States of America and Australia. A conclusion is made about the justification for involving the public in decision-making at the stage of setting the problem and planning the development of the corresponding solution for a full consideration of alternative solutions, including consideration of several such options simultaneously. It is noted that the analysis of foreign experience shows the presence of significant potential for the development of greening tools in the field of public procurement, and also demonstrates examples for the development and implementation of effective mechanisms for green procurement, adapting them to the legal system and economic structure of the country. The authors emphasize that public participation in decision-making, access to information and justice have a constitutional and legal content and can be traced in industry legislation. Attention is paid to the Basic Law of the state, which acts as a conceptual document and enshrines the value and legal vectors of regulating public relations.
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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 | 0.097 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.009 | 0.053 |
| Scholarly communication | 0.025 | 0.013 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 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".