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Record W2766212698 · doi:10.5539/jas.v9n11p76

The Revealed Comparative Advantage Index of Brazilian Natural Honey

2017· article· en· W2766212698 on OpenAlexvenueno aff
Maristela Franchetti de Paula, Humberto Ângelo, Alexandre Nascimento de Almeida, Éder Pereira Miguel, Pedro G. A. Vasconcelos, Ari Schwans, Marcio Alexandre Facini, Ademir Juracy Fanfa Ribas, Raquel S. Pompermeyer

Bibliographic record

VenueJournal of Agricultural Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Food Sciences
Canadian institutionsnot available
Fundersnot available
KeywordsRevealed comparative advantageComparative advantageChristian ministryIndex (typography)CommodityBusinessOrder (exchange)Competitive advantageInternational tradeAgricultural economicsInternational marketCompetition (biology)EconomicsGeographyMarketingBiologyEcologyPolitical scienceComputer scienceFinance

Abstract

fetched live from OpenAlex

Natural honey is considered a valuable forestry product not only for biodiversity but also to its conservation functions. Besides, it is an important exported commodity. In this study, the performance of Brazilian natural honey exported products were evaluated with specific focus on determination of their competitiveness in the international market. This article aimed to calculate the Revealed Comparative Advantage Index (RCA) of Brazilian natural honey, from 2000 to 2015. The sources consulted are SEBRAE, IBGE, Brazilian Ministry of Development, Industry and Foreign Trade and the United Nations Commodity Trade Statistics Database (UN COMTRADE). The methodological procedure used was Balassa’s Revealed Comparative Advantage Index in order to estimate the competitiveness measure. The results demonstrated that Brazil was competitive in natural honey exported products during the period from 2002 to 2015. Considering the outcomes, based on the indexes it is possible to affirm that Brazilian natural honey is competitive and the country displays enough positive characteristics and productive capacity to amplify its participation in new international commercial markets.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0030.000
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 head0.022
GPT teacher head0.276
Teacher spread0.253 · 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 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

Citations6
Published2017
Admission routes1
Has abstractyes

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