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WORLD EXPERIENCE IN ADMINISTRATIVE AND LEGAL SUPPORT OF FOOD SECURITY

2024· article· en· W4407335150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBaltic Journal of Economic Studies · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
FundersInternational Fine Particle Research Institute
KeywordsBusinessFood securityAdministrative lawMarketingPublic administrationPublic relationsPolitical scienceAgricultureGeography

Abstract

fetched live from OpenAlex

The purpose of the study is to improve the legal support of food security in Ukraine, taking into account foreign best practices in this area. The subject of the research is a comparative analysis of the administrative and legal support of food security in the USA, Canada, Japan and the EU countries, according to the areas of state support and development of the agricultural sector, state social policy and social support of the population, and state regulation of product quality assurance. The generalisation of trends in foreign experience can be used to improve the administrative and legal regulation of the food security system of Ukraine. The methodological background of the study is a combination of theoretical and general scientific methods: analysis, synthesis and comparison, theoretical and logical generalisation. The study systematises the strategic directions of state regulation of food security in foreign countries (in particular, the United States, Canada, Japan, and the European Union) in accordance with the directions of state regulation of the agricultural sector, state social policy and social support of the population, and state regulation of product quality. Each country has a unique approach to food security, depending on domestic policies, resources and global market conditions. However, all the countries analysed share the common goal of ensuring safe, high-quality and affordable food for their populations, while developing a sustainable agricultural sector. This study analyses the food security challenges and threats facing Ukraine during the Russian-Ukrainian war (2022-2024). These factors contributed to the adoption of administrative and legal strategic decisions aimed at improving food security and economic sustainability of the country, namely: the law that restored the work of the State Land Cadastre, joining the signing of the Roadmap for Global Food Security; the Food Systems Transformation Plan for the period up to 2030; the Resolution "On Ensuring Stable Operation of Food Producers under Martial Law"; the National Food Security Platform; the draft National Target Programme for Land Use and Protection until 2033 and other regulatory documents aimed at stabilising the agricultural sector, restoring land use and improving the country's food security in times of war. Conclusion. Based on the research, Ukraine has a unique opportunity to improve the administrative and legal support of food security, using the foreign experience of progressive countries with a high level of the Global Food Security Index. At the same time, Ukraine is experiencing a crisis related to the consequences of the Russian-Ukrainian war, in particular: deterioration of food security; reduction of the population's purchasing power due to higher prices for basic foodstuffs; reduction of the amount of sown areas in the agricultural sector; reduction of the country's capacity. The government has adopted a number of laws, regulations, acts and measures to improve food security and economic sustainability. The implementation of these measures is aimed at achieving the following goals: replenishing the agricultural market by supporting producers; restoring food industry enterprises; ensuring the availability of food for all segments of the Ukrainian population; strengthening food security by replenishing state reserves with food; creating a food security monitoring system; prioritising the de-mining of agricultural land; adapting to climate change, etc.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.314
Threshold uncertainty score0.113

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.053
GPT teacher head0.299
Teacher spread0.245 · 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