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Record W4297237882 · doi:10.1007/s13563-022-00343-1

The global mining industry: corporate profile, complexity, and change

2022· article· en· W4297237882 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMineral Economics · 2022
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsQueen's University
FundersUnited Nations University World Institute for Development Economics ResearchUniversity of OxfordJohns Hopkins University
KeywordsListing (finance)BusinessCorporate social responsibilityMining industryPublic relationsPolitical science

Abstract

fetched live from OpenAlex

Abstract The continuation and increasing importance of mining is inevitable as society embraces both the transition to a low-carbon economy and application of circular economy concepts. However, across many parts of society, there is an ongoing sense that those who are carrying many of the costs and risks related to mining particularly over the long term (often host communities and countries) are not seeing a level of benefit that seems fair. In contrast, there is frustration within the industry that mining is not being given due credit for the importance of its role in contemporary society by those who would criticize industry practices. Over the past several decades, dozens of initiatives aimed at strengthening mining’s social and environmental performance have been mounted from both within and outside the industry. These generally depend on a “leadership-trickle-down” change model. While progress has been achieved, the society-industry trust deficit continues. The global mining community comprises a corporate core and a complex range of other surrounding interests. We suggest that some key questions regarding the nature of this community and its appetite and capacity for change have not been explored thus impeding the effectiveness of change management. We offer (1) an estimate of the number of companies that lie at the core of the global mining community: some 25,000 operating in about 140 countries (using data from the mid-2010s); (2) a profile of these companies as an initial step towards understanding the “culture” of the global mining community; and (3) a listing of additional complexities and observations important to bringing global-wide improvement to mining’s social and environmental performance. We argue that building on work to date, a fresh approach is required. We are calling for a dialog to reflect on the ideas presented here, refine them as appropriate, and develop the needed strategies and action plans. Such a process must build from a comprehensive understanding of the global mining community and its culture. It must be collaborative in nature and involve not only the range of mining companies but also with surrounding interests and governments. If this is not done, the change that is needed to align actions of all mining actors with social values will not occur and the trust deficit will remain.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.329

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 head0.067
GPT teacher head0.217
Teacher spread0.150 · 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