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Record W3001288142 · doi:10.3138/chr.2019-0010

Selling off the Crown Jewels: Socialization of Costs and Privatization of Profits in the Canadian Isotopes Industry

2020· article· en· W3001288142 on OpenAlexaffvenueabout
Mahdi Khelfaoui

Bibliographic record

VenueCanadian Historical Review · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical and Economic history of UK and US
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCorporationAtomic energyPoliticsInvestment (military)Government (linguistics)FinanceDivestmentBusinessEconomicsMarket economyPolitical scienceLawSociology

Abstract

fetched live from OpenAlex

This article explores the privatization process of a nuclear Crown corporation, the Radiochemical Company (rcc), under Brian Mulroney’s two Progressive Conservative governments. The rcc specialized in processing and commercializing radioactive isotopes for the medical market, an industry in which it was a major global player. Between 1984 and 1991, several stakeholders, including the rcc’s parent company Atomic Energy of Canada Limited, the Ministry of Energy, Mines and Resources, the Ministry of Finance, and the Canada Development and Investment Corporation, tried to define and shape the terms of the privatization. As a result, the process did not follow a straightforward path since it triggered conflicting political and strategic interests. Through the rcc’s case, this article provides a comprehensive account of the institutional mechanisms that were at play during the application of the Conservatives’ divestiture policy. Contrary to what the government’s rhetoric suggested, privatizing the rcc did not put an end to public spending in the medical isotopes business. The opposite actually happened as the rcc’s sale resulted in socializing the costs and privatizing the profits of this lucrative branch of the Canadian nuclear industry.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.281
Teacher spread0.215 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations2
Published2020
Admission routes3
Has abstractyes

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