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Record W7000692089

Froth Flotation and Kimberley, B.C. The Role of Technology in the Transition Between Mining Camp and Community

2010· article· en· W7000692089 on OpenAlexfundno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2010
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
FundersThompson Rivers University
KeywordsResource (disambiguation)Human settlementWork (physics)Resource depletionExploitation of natural resourcesMineral resource classificationInformal settlementsIndustrial Revolution
DOInot available

Abstract

fetched live from OpenAlex

Throughout the industrial age, the search for mineral resources has led to the creation of many\ntemporary resource extraction settlements, the vast majority of which never become long-term\ncommunities. For those who do, there is a critical point at which they transform from a largely singlesex work camp into a community with families and extended social and employment networks. While much research has been done on the growth and development of resource communities, far less has focused on this transitional period, and one aspect in particular has been especially neglected – the role of mining technology. This article examines the invention and application of one extremely influential\npiece of technology, the differential froth flotation method of ore separation, and its impact on the hardrock mining communities. Due to this technology’s extension of mine lifespan, long-term settlements could be developed around mine sites. In the case of twentieth century North American resource communities, this transition was also aided by research on crime and social trends that suggested advantages to living in smaller urban or suburban centers. This in turn influenced public policy that created a favorable atmosphere for the growth and survival of many small cities that had originated as resource extraction camps. This article examines these various contributing factors by using the example of a particular British Columbia community.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.749

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 integrity0.0000.001
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 head0.002
GPT teacher head0.154
Teacher spread0.151 · 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 designOther design
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

Citations0
Published2010
Admission routes1
Has abstractyes

Explore more

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