The Shrinking Mining City: Urban Dynamics and Contested Territory
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
Abstract Shrinking mining cities — once prosperous settlements servicing a mining site or a system of mining sites — are characterized by long‐term population and/or economic decline. Many of these towns experience periods of growth and shrinkage, mirroring the ebbs and flows of international mineral markets which determine the fortunes of the dominant mining corporation upon which each of these towns heavily depends. This dependence on one main industry produces a parallel development in the fluctuations of both workforce and population. Thus, the strategies of the main company in these towns can, to a great extent, determine future developments and have a great impact on urban management plans. Climate conditions, knowledge, education and health services, as well as transportation links, are important factors that have impacted on lifestyles in mining cities, but it is the parallel development with the private sector operators (often a single corporation) that constitutes the distinctive feature of these cities and that ultimately defines their shrinkage. This article discusses shrinking mining cities in capitalist economies, the factors underpinning their development, and some of the planning and community challenges faced by these cities in Australia, Canada, Japan and Mexico. Résumé Les villes minières en décroissance, localités autrefois prospères qui desservent un site ou un réseau de sites d'exploitation minière, se caractérisent par un long déclin de leur population et de leur économie. Beaucoup d'entre elles connaissent des périodes de croissance et de décroissance, à l'image des hauts et des bas des marchés miniers internationaux dont dépend la prospérité du groupe minier prépondérant dans chacune de ces villes. Cette dépendance vis‐à‐vis d'une seule activité industrielle génère une évolution parallèle de la main‐d'œuvre et de la population. Dans ces villes, les stratégies de l'entreprise principale peuvent donc très largement déterminer les aménagements futurs et influer sur les plans de gestion urbaine. Conditions climatiques, savoirs, éducation, services de santé et réseaux de transport sont des facteurs importants dans le mode de vie local, mais ce sont les transformations qui vont de pair avec l'évolution des opérateurs du secteur privé (souvent une seule grosse entreprise) qui constituent le trait distinctif de ces villes minières et détermine finalement le ‘rétrécissement’ urbain. Cet article analyse les villes minières en décroissance dans les économies capitalistes en s'attachant aux facteurs fondamentaux de leur développement et à certains enjeux, propres à l'aménagement et à la communauté, auxquels ces villes sont confrontées dans leur pays respectif (Australie, Canada, Japon et Mexique).
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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 | 0.003 | 0.001 |
| 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 | 0.001 |
| 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