“Steering Our Own Ship?” An Assessment of Self-Determination and Self-Governance for Community Development in Nunavut
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Northern Review 41 (2015): 157–180Climate change, the global demand for energy, and the depletion of easily accessible natural resources has led to an increase in mining activities in the Arctic, including in Nunavut, a region rich in resources but remote in comparison to the rest of Canada. Nunavut is a predominantly Inuit socio-political region created in 1999 via the Nunavut Act and the Nunavut Land Claims Agreement (NLCA) (1993). The NLCA also enshrined the Inuit right to manage the region’s minerals and other natural resources. Yet, despite this power to “steer their own ship,” Inuit communities struggle to maximize the benefits from resource development. Pond Inlet is a coastal hamlet on Baffin Island close to the newly operational Mary River Iron Ore Mine, an open pit mine with the potential to bring significant economic opportunities to the region. Using a framework developed by the Harvard Project on American Indian Economic Development, a case study of Pond Inlet highlights factors that contribute to and hinder Arctic Aboriginal communities’ successful local development. A total of 47 semi-structured interviews were conducted with key informants in Pond Inlet and the territory’s capital, Iqaluit. Findings underscore the importance of Indigenous community self-determination, effective and culturally relevant governing institutions, and clear visioning for the future. In Pond Inlet, key barriers to maximizing local benefits relate to institutional and governance challenges. Evidence from this study suggests that Pond Inlet will better succeed with local community development by strengthening its governance mechanisms to support the goals of self-determination.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it