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Record W4395457751 · doi:10.1515/9780889779709-002

PREFACE

2023· book-chapter· en· W4395457751 on OpenAlexaboutno aff
Eric Cline

Bibliographic record

VenueUniversity of Regina Press eBooks · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Potash is a vital resource.Without it, people go hungry.That fact will become only more important as the world population continues to grow.A detailed chronicle of the early days of developing Saskatchewan's rich and unparalleled potash resource, as well as the creation and performance of the Potash Corporation of Saskatchewan (pcs), is ably presented in John Burton's Potash: An Inside Account of Saskatchewan's Pink Gold, published by the University of Regina Press in 2014.Some of that history is summarized here to inform and contextualize the discussion of potash mining in Canada in the last few decades.This book's focus is on how the current ownership, operation, and taxation of the potash industry serves the public interest in providing jobs, maximizing economic development in Saskatchewan, and increasing the benefits to the Saskatchewan people from the sale of their potash resource, especially during times of high demand, prices, and profits, as has been the case for the past sixteen years or so.During my terms as Saskatchewan's minister of finance (1997)(1998)(1999)(2000)(2001)(2002)(2003)) and minister of industry and resources (2003)(2004)(2005)(2006)(2007), I interacted regularly with potash company executives and was directly involved in all public policy decisions related to the mining sector.After retiring from politics, I worked in the mining sector, including six years as a vice-president of K+S Potash Canada.I also served on the boards of both the Saskatchewan Mining Association and the Saskatchewan Potash Producers' Association.My perspective as an author is naturally both informed and influenced by my experience as an insider in both public policy-making within government and as a corporate executive in the mining sector, as well by my personal and political views.My perspective is also greatly influenced by

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)0.006
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: Editorial · Consensus signal: none
Teacher disagreement score0.591
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.5910.412

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 head0.025
GPT teacher head0.170
Teacher spread0.145 · 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
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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