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Record W4205240674 · doi:10.53604/rjbns.v16i2_17

Pål Thonstad Sandvik, Multinationals, Subsidiaries and National Business Systems: the Nickel Industry and Falconbridge Nikkelverk

2014· article· en· W4205240674 on OpenAlexaboutno aff
Artur Lakatos

Bibliographic record

VenueThe Romanian Journal for Baltic and Nordic Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMetallurgy and Cultural Artifacts
Canadian institutionsnot available
Fundersnot available
KeywordsSubsidiaryNorwegianCorporationContext (archaeology)RefineryBusiness historyPoliticsUnit (ring theory)HistoriographyCapital (architecture)ManagementBusinessMultinational corporationEconomyEngineeringEconomicsPolitical scienceFinanceLawHistory

Abstract

fetched live from OpenAlex

Norwegian historiography has brought some really relevant contribution in the field of economic history. This is especially true in the direction of business history, which approaches economic issues through the history of the development of companies, of business and development in the mirror of economic efficiency. Such an example is this present monograph signed by Professor Pål Thonstad Sandvik, having as main subject the development of a subsidiary of the Canadian Falconbridge company, the nickel refinery of Kristiansand. The complex synthesis has in its focus the mentioned refinery, dealing at the same time with economic and social processes related to this industrial unit, but not only: its evolution is also placed in the socio-economic and political context of international trade. The reader can follow the development of the refinery step by step, in a chronological succession of events, with all of its “good” and “bad” moments, from its foundation until the Norwegian Øyvind Hushovd became the president of the Falconbridge corporation during the 1990s, not only because of the efficiency of the refinery from Kristiansand, but also due to the increase of the Scandinavian capital within Falconbridge.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
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 head0.076
GPT teacher head0.354
Teacher spread0.278 · 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.

Study designTheoretical or conceptual
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

Citations0
Published2014
Admission routes1
Has abstractyes

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