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Record W4391464746 · doi:10.5874/jfsr.23.30.3_8

Structural Analysis of the Food System of Imported Rapeseed

2023· article· en· W4391464746 on OpenAlexaboutno aff
K. Yagi, Shinji TAKADA, Takashi FUNATSU, Toyohiko Matsubara

Bibliographic record

VenueJournal of Food System Research · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicOutsourcing and Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

This study examines four key aspects of stable oilseed procurement, providing insights into the overall structure of the rapeseed food system imported from Canada to Japan. Firstly, we present an overview of the current situation and challenges associated with the procurement of imported rapeseed in Japan. Secondly, we clarify the vertical coordination system, shedding light on potential future access to rapeseed export channels from Canada. Thirdly, we analyze the decision-making process for determining optimal quantities of imported rapeseed and explore alternative options. Lastly, we examine power imbalances within the vertical stages of the rapeseed food system from an equity perspective. The study concludes with policy implications as follows: (1) Under a trading structure with price mechanism functions, it is necessary to create an environment in which the Japanese vegetable oil industry can pass on high raw material prices to consumers to ensure competitive and stable raw material procurement; (2) It is essential to establish stable and close political relationships between countries; (3) When considering alternative oil and fat products, confirming Japanese consumer evaluations is necessary; and (4) Since the expansion of biodiesel production in various countries could be detrimental to Japan's food security, its merits and demerits must be evaluated.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.070
GPT teacher head0.306
Teacher spread0.236 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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