Toward Sustainable Development in the North: Exploring Models of Success in Community-Based Entrepreneurship
Bibliographic record
Abstract
This article intends to achieve a better understanding of economic and social development in the remote, northern regions in Saskatchewan. The authors reviewed development models that were employed by various communities. By benchmarking the practices documented and reported in the extant literature, the authors discussed the need for comparative empirical research for further development of the theory on northern development. Following a comparative case analysis method, the authors selected cases that were theoretically and empirically comparable to Northern Saskatchewan, re-examined the reported relationships among relevant factors, and categorized the themes regarding developmental strategies and their resulting outcomes. These cases were from communities in Canada, the US, and Northern Scandinavia. While there was general agreement on what constituted “good practices” for regional economic and social development, there was no consensus or panacea for success. Each case was heavily embedded in a set of contextual circumstances. Some communities had undertaken different strategies to achieve the same kind of outcomes, while similar strategies have produced drastically different results in other communities.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".