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Record W621571413 · doi:10.7202/702250ar

L’Union soviétique et les minerais stratégiques : Erreurs et vérités

2005· article· en· W621571413 on OpenAlexaffvenue
Miron Rezun

Bibliographic record

VenueÉtudes internationales · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicRussia and Soviet political economy
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSoviet unionCurrencyPolitical scienceEconomyEconomicsLaw

Abstract

fetched live from OpenAlex

This is an analysis of the major strategic minerals (sometimes called strategic materials), including some of the precious metals, which are vital to the Western economies. It focuses primarily on Soviet strategic minerals policies and examines the conflicting hypotheses for and against a resource war waged by the Soviet Union. The conclusions reached on the strength of the evidence so far is that Soviet policies have been chiefly economic and motivated by economic self-interest ; the Soviet Union is seen as an eager competitor for markets to acquire hard currency and not as a power eager to deprive the West of critical resources. A case is also made for the increasing importance of materials science, ocean mining and substitution, which is likely to make the West, including the USSR, invulnerable to supply disruptions in the future.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.007
Scholarly communication0.0080.004
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.368
Teacher spread0.324 · 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
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

Citations1
Published2005
Admission routes2
Has abstractyes

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