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Record W2047964077 · doi:10.1080/14041040701390773

The Future of Raw Material Prices and the World Economy

2007· article· en· W2047964077 on OpenAlexaboutno aff
Sadi UZUNOĞLU, Ayhan AYTAÇ, Ahmet Atakişi

Bibliographic record

VenueRaw materials report/Minerals & energy./Minerals & energy · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Productivity
Canadian institutionsnot available
Fundersnot available
KeywordsRaw materialEconomicsQuarter (Canadian coin)World economyMonetary economicsEconomyGeography

Abstract

fetched live from OpenAlex

Raw material prices dramatically increased in the last quarter of 2001. It has been argued that growth of the world economy and expansion of foreign trade are major effective factors in increasing raw material prices. On the other hand, from the last quarter of 2001, growing political instability and regional battles have also placed pressure on prices. In reality, the uncertain trend of raw material prices is not today's issue; the problem has been present in recent centuries. However, as a result of the collapse of the world monetary system in the 1970s, uncertainty of exchange rates and interest rates have increased these fluctuations of raw material prices and have had a negative effect on the world economy. Our aim is to evaluate the issue of raw material prices in the light of developments in the world economy and to expose the uncertainty and the risks inherent in projections of raw material price fluctuations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.006
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.205
Teacher spread0.196 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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
Published2007
Admission routes1
Has abstractyes

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