Exploring complexity in changing practices of care : a mixed methods inquiry into rights, relations, and knowledge in protected area conservation
Bibliographic record
Abstract
Commonly described as the cornerstone of conservation, protected areas contribute immeasurably to supporting flourishing ecosystems and human wellbeing, and are crucial tools to address the accelerating biodiversity crisis. Yet conventional exclusionary approaches have frequently proven ineffective and inequitable. Accordingly, there is a pressing need for conservation actors to make decisions considering diverse knowledge and values, under conditions of high uncertainty. This dissertation is concerned with the nature of these decisions as they are unfolding in practice, and their entanglements with structures of power, patterns of change, and diverse ways of knowing the human and other-than-human landscape. At multiple scales of decision-making –– conservation planners, community forest managers, and household resource users –– I investigate how institutional arrangements, evidentiary norms, and human-environment relationships affect stewardship. The second chapter develops a novel approach using document analysis and survey methods to assess how the Nature Conservancy of Canada applies multiple types of evidence in conservation planning, identifying evidence gaps and barriers to effective engagement with Indigenous knowledges. The subsequent empirical chapters focus on three related aspects of environmental governance in van panchayat community forests in a high mountain valley in Uttarakhand, India. Chapter 3 introduces the case study, describing how forest councils navigate their legal and customary rights and responsibilities to manage van panchayats for conservation and livelihood benefits. In the same region, the fourth chapter applies a mental models analysis approach to interview data, to illustrate complexities and patterns in how local forest managers are perceiving and responding to intersecting dimensions of change. The fifth and final empirical chapter reports on qualitative and quantitative analyses of a household survey on human-wildlife relations in the same community forests, finding that institutional responsibilities and ethics of care contribute meaningfully to norms of coexistence with wild animals despite persistent conflict. These inquiries apply a range of methodological approaches to advance theories of environmental governance in political ecology, knowledge co-production, and the human dimensions of conservation. In doing so, this work highlights the highly complex, context-specific, and changing ways in which stewarding actors care for protected areas in practice, and identifies potential pathways to support these efforts.
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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 | 0.074 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| 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".