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Record W1497957727 · doi:10.3138/jcs.46.1.75

To Market, To Market: Innovation, Canada’s Nuclear Industry, and the Case of the Nuclear Battery

2012· article· en· W1497957727 on OpenAlexvenueaboutno aff
Ian J. Slater

Bibliographic record

VenueJournal of Canadian Studies · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDefense, Military, and Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Nuclear powerJoint venturePrivate sectorAtomic energyBusinessCrewEngineeringJoint (building)FinanceIndustrial organizationEconomic growthEconomicsCommerceAeronauticsCivil engineering

Abstract

fetched live from OpenAlex

Atomic Energy Canada Limited pursued the development of a small-scale nuclear reactor intended for use in the North Warning System during the height of the Cold War. This reactor, known as the nuclear battery, was later considered as a submarine power source for the Canadian Submarine Acquisition Program (CASAP). AECL’s approach to the development of the nuclear battery was to form joint-venture partnerships with public- and private-sector companies in order to share design and development costs; however, AECL had both the funding and the in-house technical and scientific expertise to develop the nuclear battery without these partnerships. Further, the pursuit of these partnerships did not lead to success; the nuclear battery was a failed innovation. This study links the preference for joint-venture partnerships at AECL to the neo-liberal approach to innovation that swept through Canadian government and private-sector industries in the 1980s and early 1990s, as it had swept through British and American industries before it.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.139
Threshold uncertainty score0.999

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0250.026
Scholarly communication0.0140.007
Open science0.0010.004
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0080.000

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 head0.042
GPT teacher head0.234
Teacher spread0.192 · 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 designQualitative
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

Citations4
Published2012
Admission routes2
Has abstractyes

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