Investigating the role of public participation in wind energy project development in Ontario
Bibliographic record
Abstract
Over the past several decades, the scope of decision-making in the public domain has changed from a focus on unilateral regulatory verdicts to a more comprehensive process that engages all stakeholders. Consequently, there has been a distinct increase in public participation in the environmental decision-making process. While the potential benefits of public engagement are substantial in terms of identifying synergies between public and industry stakeholders that encourage project development, this participation does not come without its challenges. To meet global energy demands and fulfill ambitious targets for greenhouse gas reduction, renewable energy has received increased attention as a feasible alternative to conventional sources of energy. However, current literature on renewable energy, particularly on wind power, highlights potential social barriers to renewable energy investment. This study investigates the role of public participation by reviewing two case studies of the Ontario wind power generation market to identify the facilitators and constrainers that affected public input into wind project development in Ontario and recommends a participatory framework in the hope of improving public engagement in the wind project development decision-making process. The recommended framework in this research requires all stakeholders to reconsider their current roles in the decision-making process. The public should engage in project planning and monitor the decision-making processes to ensure that their concerns have been addressed. Developers should address public concerns through a consensus building process initiated early in their planning process. Federal and provincial governments have to reclaim their role of ongoing leadership and provide better criteria for implementation and evaluation of the public participation processes. Finally, the process requires a third party who is not only an intermediary, but also plays the role of a knowledge-broker to connect with stakeholders, share and exchange knowledge, and work on overcoming barriers. The knowledge-broker helps to fulfill the main requirement of the collaborative decision-making, which is effective communication.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".