Environmental and resource conflicts and conflict resolution practices in coastal areas of the North American Great Lakes: towards an integrated approach for policymaking
Bibliographic record
Abstract
Environmental conflicts are multi-dimensional. Individual components of environmental and resource-related conflicts are closely interlinked with other structural societal elements, including economic, social, political and cultural developments. Coastal areas are significant for people’s subsistence, as well as industrial development, cultural heritage, and waterways; therefore, they require integrated research approaches and the implementation of comprehensive strategies of resource management, dispute resolution and conflict prevention. This qualitative exploratory study contributes to the development of the field of environmental conflict resolution (ECR) by examining the perceptions and experiences of 52 key stakeholders from the coastal areas of the Great Lakes region of Canada and the United States (US) with regards to environmental and resource conflicts and conflict resolution approaches. The study invited coastal stakeholders such as environmental policymakers, researchers, academics, educators and NGO members to share their perceptions, images, experiences and knowledge about environmental and resource conflicts and conflict resolution practices in the coastal areas of the Great Lakes. The framework of this holistic study integrates public policy, alternative dispute resolution, conflict analysis, project evaluation, dialogue and public participation, education and other creative interventions into an inclusive strategy of integrated environmental and resource management of coastal areas. Analysis of the study participants’ responses revealed several key findings. First, the multi-dimensional character of environmental and resource conflicts and the wide range of coastal stakeholders involved necessitate creating spaces for dialogue and communication among coastal stakeholders, which may facilitate relationship building and encourage collaborative problem solving and constructive conflict resolution. Second, establishing links between science and policymaking within environmental and resource management, as well as introducing conflict resolution education for coastal stakeholders, may significantly enhance the capacity of coastal stakeholders in ECR. Third, coastal stakeholders in the Great Lakes have an extensive and wide-ranging existing local knowledge, experience and expertise in resolving environmental and resource conflicts. Fourth, a conflict resolution system’s design developed in this study may serve as an integrated framework for the analysis and resolution of environmental and resource conflicts. This ECR system design involves such important components as conducting conflict and stakeholder analysis; identifying the root causes of conflict; bringing conflict participants together to discuss resolution options; and building in continuous evaluation of environmental conflict resolution processes.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".