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Record W2143434392 · doi:10.24908/ijesjp.v3i1.5223

A New Vision for Mining Education – First Steps

2014· article· en· W2143434392 on OpenAlexaffvenueabout
Anne Johnson, Ursula Thorley

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2014
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsTransformative learningCurriculumContext (archaeology)SituatedEngineering ethicsSociologyPolitical scienceEngineering managementPublic relationsPedagogyEngineeringComputer scienceArtificial intelligenceArchaeologyGeography

Abstract

fetched live from OpenAlex

This paper narrates the experience of a Canadian university in reorienting its mining curriculum towards the goal of producing engineers who are sensitive to context. The authors acknowledge industry’s historical association with environmental degradation and imperialism, but counter that mining is necessary to provide the materials of civil infrastructure, particularly that required to reduce green-house gas emissions. They also point to the potential for mining projects to rejuvenate communities, by providing the revenues that support self-determination, suggesting that more equitable distribution of impacts and benefits may be achieved through engineering design that is better informed and sensitive to community perspectives.To promote such an approach to engineering design, the Robert M. Buchan Department of Mining at Queen’s University has instituted a program of curriculum re-positioning that is informed by theories of situated and transformative learning. This paper traces the first steps in the development and execution of curriculum that supports the development of student awareness of context and culture and a new contextually-sensitive approach to professional practice.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score0.311

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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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 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

Citations4
Published2014
Admission routes3
Has abstractyes

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