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Record W2552868530

Assessing the legacy of the pine point mine: post-industrial land cover and land use

2015· dissertation· en· W2552868530 on OpenAlexfundaboutno aff
Emma LeClerc

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2015
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsLand reclamationGeographyLand useSustainabilityCultural landscapeNuclear decommissioningSustainable developmentIndustrial ecologyAbandonment (legal)Environmental planningEcologyEnvironmental resource managementEnvironmental sciencePolitical scienceEngineeringArchaeology
DOInot available

Abstract

fetched live from OpenAlex

While mining is a major component of the northern Canadian economy, including the contemporary mixed economy of Aboriginal communities, it often leaves legacies of environmental and economic transformation that persist after closure. The legacies of historical mines in northern Canada challenge industry claims of sustainability. This thesis addresses how industrial mineral development and closure continue to affect local environments and economies after abandonment. The abandoned Pine Point mine in the Northwest Territories provides a case study for explaining the ongoing relationships among land cover, land use, and the post-industrial landscape. Drawing from landscape ecology and micropolitical ecology, I adopt an interdisciplinary approach to examine environmental and socioeconomic changes in the wake of industrial development and closure at Pine Point. The results show that passive reclamation is not sufficient for restoring ecological function in a subarctic environment. Land use, however, persists as land users adapt to the post-industrial landscape despite grave concern about its environmental condition. If mining is to be considered sustainable, decommissioning and reclamation must explicitly account for long-term environmental transformation as well as ongoing post-industrial land use, particularly in Aboriginal contexts.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.365
Teacher spread0.278 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2015
Admission routes2
Has abstractyes

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