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Record W2764551649

Competitiveness of Mediterranean Countries in the Olive Oil Market

2010· article· en· W2764551649 on OpenAlexaboutno aff
Berna Türkekul, Cihat Günden, Canan Abay, Bülent Mìran

Bibliographic record

VenueNew medit: Mediterranean journal of economics, agriculture and environment · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsOlive oilMarket shareBusinessProduction (economics)International marketDomestic marketEuropean marketInternational tradeWorld marketAgricultural economicsEconomyEconomicsInternational economics
DOInot available

Abstract

fetched live from OpenAlex

This study employs constant market share analysis to determine the competitiveness of Turkey, Spain, Italy, Greece and Tunisia, i.e. the world’s primary olive oil producers, in markets in the USA, Australia, Canada, Brazil and Japan in the periods 2000-2004 and 2005-2008. The analysis shows that during the periods covered, Tunisia was the most competitive in the target markets. All countries showed decreased competitiveness during the periods analyzed. In the same period, although Greek export to target markets has increased, the competitiveness of Greece was adversely affected due to a decrease in its market share. The success in achieving sustainable and permanent international competitiveness in the olive oil market depends on production, organization and trade policies. Especially for Turkey, export strategies that consider the consumer demands and expectations in the destination markets should be developed. Finally, Turkey should introduce a new image for its national production.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.181
Teacher spread0.168 · 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 designObservational
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

Citations31
Published2010
Admission routes1
Has abstractyes

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