Breaking New Trail? First Nations and Municipal Government Cooperation in Rural Yukon
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
Rural communities in the Yukon tend to be very small, most with fewer than 1,000 people, with mixed Indigenous and non-Indigenous populations. Although small, these communities face economic, social, and environmental issues similar to larger centres. These problems are complex and require a collective response from multiple governments or organizations. This research project explored the factors of inter-organizational collaboration and examined the status of cooperation between Self-Governing First Nations (SGFNs) and municipalities in rural Yukon in order to understand the factors that strengthen collaborative processes and any barriers to these processes. The project involved interviews with six key informants who are, or were, directly involved with a municipality, territorial government, or an SGFN. The research found that while most SGFNs and municipalities engage with each other, the trend is towards minimal cooperation, although relationships are improving slowly. All respondents agreed that SGFNs and municipalities in rural Yukon should collaborate more, for reasons including the need to make the best use of resources and social justice such as reconciliation. Frequently cited barriers to collaboration include a lack of human resource capacity and staff turnover. Other barriers are community histories and Indigenous and non-Indigenous relationships. The enabling factor of common understanding has some unique features in the Yukon. The region is a complex myriad of jurisdictions—territorial, First Nations, and municipal governments—with conflicting, competing, and separate mandates. However, the informants felt that a common understanding for First Nations and municipalities should be working together to benefit their entire communities.
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 | 0.001 | 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 | 0.002 | 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