Community politics, governance, and land-use planning in Nunavut: Two decades of controversy over the Nunavut Land Use Plan.
Bibliographic record
Abstract
Co-management, the concept that natural resource management is more effective and equitable when governments and local resource users work together, has become increasingly institutionalized in the Canadian territories. This thesis looks at one particularly ambitious application of the co-management principle: the Nunavut Land Use Plan process. Despite over a decade of work and multiple drafts, the Nunavut Planning Commission has been unable to create a plan that is close to approval. This failure illustrates a gap in academic studies of natural resource management processes involving the state and Indigenous peoples in Canada. While these have largely focused on the management and valuation of knowledges, the policy development aspect and the actual implementation are equally important. Implementation and policy making remain primarily the domain of the state, and even in cases where policy-makers are motivated by progressive aims, this is not only colonial, but ineffective. Through the Nunavut Land Use Plan process has involved the collection and consideration of Inuit knowledge, and the Nunavut Planning Commission has demonstrated a commitment to planning approaches that limit the destructive excesses of industrial capital, the decision-making process that produces the plan is opaque, centralized and technical. This is a key reason for the failure of the planning process. The colonial-modernist wildlife and human management policies introduced in the Canadian North during the mid-20th century failed, and progressive initiatives run by centralized organizations in the rationalist, technocratic tradition of policy making are similarly prone to failure despite their aims. In places like Nunavut that are sparsely populated and have a strained public service, there needs to be a greater shift towards community-based policy making and implementation. While there are some positive steps in this direction occurring in Nunavut, more resources and capacity should be provided to communities if planners and academics expect there to be policies that respect the knowledges and understandings of communities, or even to simply achieve their intended purpose.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.032 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".