Studies on the Effects of Mine Closures in Canada
Bibliographic record
Abstract
This dissertation explores the socioeconomic impacts of mine closures in Canada, focusing on the vulnerabilities that arise within local economies and the political economy implications of industrial changes. Through a combination of historical, quantitative, and qualitative analyses, the research provides a comprehensive understanding of the effects of mine closures on employment, municipal finances, and community livelihood. The studies provide key foundations to the analysis of mining in Canada. First, I trace back the history of the mining in the country by presenting four regimes to comprehend industrial changes and continuities since 1859. This is the first longitudinal analysis made of the industry at the Canadian level. Second, I construct a novel database of mining activities from 1950 to 2023, which both offers an essential base for the rest of the dissertation and can be used by other researchers. The dissertation then estimates the dynamic effects of a closure and draws a multifaceted understanding of community livelihoods in resource-dependent regions. The findings reveal that the repercussions of mine closures extend beyond immediate job losses at the mine. I uncover the large spillover into employments in other industries and the constraints on fiscal capacities of mining municipalities in the long run. I demonstrate the persistence of the effects on local labour markets and the significant challenges in maintaining essential services following mine closures. Overall, this dissertation contributes valuable insights for policymakers, stakeholders, and scholars interested in the sustainable development of mining communities and the economic history of regional structural transformation. With respect to necessary transition toward sustainable economies, I underscore the importance of linkages and economic structures to mitigate the adverse effects of mine closures and the need to be critical to the sustainable mining discourse given the history of the industry in Canada.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".