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Record W2053090525 · doi:10.14430/arctic4202

All That Glitters: Diamond Mining and Tłįchǫ Youth in Behchokǫ, Northwest Territories

2012· article· en· W2053090525 on OpenAlexvenueaboutno aff
Colleen Davison, Penelope Hawe

Bibliographic record

VenueARCTIC · 2012
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityGeneral partnershipContext (archaeology)PoliticsEthnographyPolitical scienceGeographyEconomic growthArchaeologyLaw

Abstract

fetched live from OpenAlex

Currently, Canada’s northern territories have three active diamond mines and one mine under construction, and one mine has recently closed. In response to local concerns, and in partnership with members of the Tłįchǫ First Nation, this ethnographic study examines the positive and detrimental impacts of diamond mining on youth in Behchokǫ, Northwest Territories, using data collected from intensive fieldwork and participant observation, focus groups, interviews, and archival documents. The study of mining impacts remains a complex and contested field. Youth in Behchokǫ experience both negative and positive effects of mining. Diamond mining companies are places of employment and act as community resources; their development has influenced the transience of individuals in the region, the identity and roles of family caregivers, the motivation of students, the purpose of schooling, and the level of economic prosperity in some (but not all) families. The diverse impacts of these changes on the health of northern individuals and communities can be understood only within the broader context of social, economic, political, and environmental changes occurring in the Arctic today. Results of this study help inform ongoing efforts by those in Behchokǫ and the Northwest Territories to monitor the effects of diamond mining and maximize the potential benefits for local people, including youth.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.203
Teacher spread0.184 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations17
Published2012
Admission routes2
Has abstractyes

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