MétaCan
Menu
Back to cohort

A comparative overview of legal frameworks governing water use and waste water discharge in the mining sector

2017· article· en· W2772482943 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueResources Policy · 2017
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessChinaWater supplyEnvironmental planningResource (disambiguation)Water resourcesCopper miningNatural resource economicsGeographyEnvironmental sciencePolitical scienceEnvironmental engineeringLawEconomics

Abstract

fetched live from OpenAlex

Mining operations require access to a secure and stable water supply. Obtaining water use and discharge licenses has become increasingly challenging for mining companies in many resource rich jurisdictions. This can be attributed in part due to competing water uses in water scarce regions and pollution caused by existing and legacy mines. This report provides a comparative review of the water management regulatory frameworks of some of the largest gold and copper producing jurisdictions. The jurisdictions reviewed include Australia (Western Australia), Canada (British Columbia), Chile, China, Peru, the Philippines, South Africa, and the United States (Alaska, Arizona, Nevada and New Mexico). Interviews of mining company representatives working on water management issues complement the legal review to highlight the perceived regulatory risk by investors of the analyzed jurisdictions.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.347

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 head0.046
GPT teacher head0.285
Teacher spread0.238 · 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