Public Participation in Energy and Natural Resources Development: A Theory and Criteria for Evaluation
Bibliographic record
Abstract
The paper focuses on the theoretical foundations of public participation in environmental decision-making and natural resources management, and develops general criteria to assess the effectiveness of both processes and results of participatory proceedings. The foundations of public participation and the justifications for its application are outlined. Habermas’ theory of communicative action is used to describe an ideal model of public participation. The author’s concepts of fairness and competence are used to shape the notion of effective participation. The study concludes that public participation is one important instrument to improve public policies related to environmental conservation and natural resources management. The proposed criteria incorporate ideas such as previous consensus on the rules of the debate, the increase of citizens’ social and political capital, the enhancement of participants’ autonomy, and the use of traditional and community knowledge. The appendix includes an analysis of the European Convention on Access to Information, Public Participation in Decision-Making and Access to Justice in Environmental Matters (the Aarhus Convention), based on the criteria proposed in the paper.
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 | 0.199 | 0.264 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.020 | 0.020 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.018 | 0.014 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".