Experiences of Opportunity in the Northern Resource Frontier
Bibliographic record
Abstract
The Northern Review 41 (2015): 181–206Resource booms, including those currently occurring in northern Canada, are anchored in narratives of economic opportunity. As a consequence, the Northwest Territories, Yukon, and Nunavut are currently seeing an increase in immigration from some non-traditional source countries of the global South. Those who arrive in Yellowknife and Whitehorse have different expectations of experiences of the North. Relatively little literature has explored the ways in which place is being constructed by such new Canadians. Where do these notions of place and place identity in northern communities fit within broader and dichotomous discourses of the North as ”hinterland or homeland”? This article examines how transnational labour migrants position their life experiences in relation to dominant discourses of neoliberalism and resource frontier values—historically sites of economic opportunity that have valorized characteristics such as masculinity and individualism that have come to ideologically define resource-based communities. Data for this article is drawn from thirty-five narrative interviews with new Canadians who had resided in Whitehorse or Yellowknife for between three and six years on average. The results suggest that transnational newcomers into the North negotiate multiple socio-economic challenges as they engage in place making within a rapidly changing northern economy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".