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Record W3000523364 · doi:10.24908/ijesjp.v7i1.13586

A Theoretical Basis for Addressing Culture in Undergraduate Mining Education

2020· article· en· W3000523364 on OpenAlexaffvenue
Anne Johnson

Bibliographic record

VenueInternational Journal of Engineering Social Justice and Peace · 2020
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsQueen's University
Fundersnot available
KeywordsDialogicDisciplineEngineering ethicsSociologyHegemonyIndigenousCurriculumCompetence (human resources)PedagogyEpistemologySocial sciencePolitical scienceEngineeringPsychologySocial psychologyEcology

Abstract

fetched live from OpenAlex

Communicating across cultural difference is a challenge for the mining industry as its attempts to gain social licence to operate in the traditional territories of Indigenous peoples. Industry organizations affirm their intention to respect communities and to develop mutually beneficial relationships, but because an understanding of culture is not a part of the mining engineer’s expertise, this goal cannot be fully realized. The undergraduate mining curriculum could address this deficiency through a critical study of culture and development of the dialogic communication skills associated with intercultural competence. Arguing that the epistemology of engineering is problematic in the cultural encounter, this paper examines, the ways in which disciplinary culture is transmitted and mechanisms for cultural change. With the objective of producing interculturally competent mining engineers, it outlines application of critical theories to deconstruct the hegemony of engineering knowledge and of communication theories to support a culturally-competent and effective approach to knowledges.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0080.038
Scholarly communication0.0080.006
Open science0.0020.007
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations9
Published2020
Admission routes2
Has abstractyes

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Same venueInternational Journal of Engineering Social Justice and PeaceSame topicEngineering Education and Curriculum DevelopmentFrench-language works237,207