Transforming conflict over natural resources: a socio-ecological systems analysis of agricultural drainage
Bibliographic record
Abstract
Agricultural drainage is a complicated and often conflict-ridden natural resource management issue, impacting contested ecosystem services related to the retention of wetlands as well as the productivity of farmland. This research identifies opportunities to transform the conflict over agricultural drainage in Saskatchewan, Canada, towards collaboration. We report on ethnographic research informed by a conservation conflict-transformation framework to evaluate the nature of the conflict and whether drivers of the conflict operate principally at the level of disputes over discrete ecosystem services or if they reach deeper into local social circumstances and build on larger unresolved conflict(s) among groups in the region. In addition to the conflict-transformation framework, we apply the Social–Ecological Systems Framework to elicit details regarding the substantive, relational, and material dimensions of this conflict. Our research suggests that processes for governing natural resources, such as those in place for governing drainage in Saskatchewan, need to have mechanisms to facilitate relationship building and shared understandings, need to be adaptable to people’s changing needs and concerns, and should focus on inclusivity and empowerment of actors to address conflict.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".