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Conditions and opportunities to realize the agricultural potential of the North

2019· article· en· W2997981662 on OpenAlexaboutno aff
Valentin A. Ivanov

Bibliographic record

VenueArctic and North · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureBusinessAgricultural economicsNatural resource economicsEnvironmental planningEnvironmental scienceGeographyEconomicsArchaeology

Abstract

fetched live from OpenAlex

The article shows the role of the agricultural sector of the North in providing the population with fresh food products, preserving the traditional way of life of the indigenous ethnic groups, sustainable de-velopment of the northern territories, and ensuring the country's food security. The organization of agriculture in the north and Arctic territories of Scandinavia, Canada and Alaska and the possibility of its use in the Russian North, considering its own rich historical experience, is discussed in the article. The generalization of agricultural practices in northern countries allows us to recommend the Scandinavian development of agriculture and, above all, the experience of Finland for the European North of Russia. Canadian model of agricultural development is of little use for the Russian North since it was designed for sparsely populated territories. The study revealed the possibilities and limitations of the development of agriculture in the North. The critical points for the socio-economic development in the agrarian sector are the availability of natural and labor resources, the possibility of organizing organic (ecological) production within the traditional industries, the industrial nature of the economy that directs significant financial resources for the industrial modernization and the integrated development of rural areas. The study also revealed the possibilities and limitations of the agricultural development of the North. The constraints of agricultural development and food self-sufficiency are explicit. They are related to extreme natural conditions, low availability of biological resources, the poor technical support of the agrarian sector, low-qualified employees and hard living conditions of peasants, unfavorable external environment, inefficient state support, unavailability of loans, and unsustainable sales of agricultural products. The changes in the agriculture of the northern territories after the All-Russian Agricultural Censuses 2006 and 2016 revealed. The results of the study serve the ground for substantiating conceptual approaches to the development of agricultural production and increasing the level of food self-sufficiency of the local population.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.719

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 studies0.0010.001
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 head0.032
GPT teacher head0.269
Teacher spread0.237 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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