The Impact of Local Participation on Community Support for Natural Resource Management: The Case of Mining in Northern Canada and Northern Sweden
Bibliographic record
Abstract
Due to its oftentimes complex, contested, and multi-scale character, natural resource management (NRM) tends to be a challenging task that has been met with various political approaches in order to meet demands for legitimacy. One approach to enhancing the legitimacy of NRM that has gained increased attention within the academic literature is the adoption of local participatory democracy in decision-making processes. Advocates of participatory democracy in NRM propose that local participation achieves the following outcomes: increased legitimacy because it ensures that local needs and priorities are successfully met; decision-making based on more complete information, which helps avoid unexpected negative outcomes; and a sense of belonging and influence among the public, leading to increased perceptions of support and partnership, as opposed to NRM which is imposed on the community. Nevertheless, comprehensive empirical studies that document how public participation affects legitimacy remain rare. Using 2015 data collected on people’s attitudes towards mining in northern Saskatchewan, Canada, and Norrbotten and Västerbotten counties, Sweden, this paper empirically assesses whether and how perceptions of local participation affect the legitimacy of mining development. In turn, this paper finds that perceived public participation does affect the public’s propensity to support mining development and this propensity is mediated by people’s perceptions of the interests present in the decision-making process, their normative beliefs concerning which actors should be allowed to participate in the decision-making process, and certain individual-level and contextual-level factors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".