MétaCan
Menu
Back to cohort
Record W3173610506

Quenching the Dragon: The Canada-China Water Crisis

2018· article· en· W3173610506 on OpenAlexaboutno aff
Robert Sandford

Bibliographic record

VenueUNU Collections (United Nations University) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsChinaContext (archaeology)SustainabilityPolitical scienceWater scarcityGovernment (linguistics)AgricultureLawHistoryArchaeology
DOInot available

Abstract

fetched live from OpenAlex

It all started out innocently enough: an airliner over the Pacific and a flight attendant passing out bottles of water. What those bottles represented, however, was the depth of China’s notorious bottled-water trade and the short-sightedness of the Government of Canada in declaring Canadian water an agricultural product that can be exported in billions of plastic bottles to China. Part environmental manifesto, part travelogue and part diplomatic odyssey, Quenching the Dragon arms readers with vital new perspectives on global hydrology and sustainability in the context of how former and current world leaders frame the most pressing environmental issues of our time. Most tellingly this book points out the remarkable similarities between China and Canada with respect to human rights as they relate to the protection and management of our ever more precious water resources. In spite of the dark undertones, this is also a work infused with hope, offering specific remedies that, if applied, will ensure that Canada doesn’t arrive at the water crisis that China and many other places in the world now face.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.051
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0160.006
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.009
GPT teacher head0.203
Teacher spread0.193 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueUNU Collections (United Nations University)Same topicTransboundary Water Resource ManagementFrench-language works237,207