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Record W2561478948 · doi:10.5539/ijef.v9n1p162

Rural Development in a Function of Local Economic Development: Case Study of Municipality of Krushevo

2016· article· en· W2561478948 on OpenAlexvenueno aff
Nikolche Jankulovski, Emiliana Silva, Katerina Bojkovska, Angjelka Jankulovska

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsAgricultureTourismChristian ministryEconomic growthRural areaSustainabilityBusinessWork (physics)Rural developmentLocal economic developmentRural tourismEconomicsGeographyPolitical scienceTourism geography

Abstract

fetched live from OpenAlex

<p>The local economic development is a process in which the local authorities and partners from the business sector and the non-governmental sector work together to improve the business climate. Through positive financial results conditions for economic growth are created and the employment opportunities are increased. Most of the municipalities in the Republic of Macedonia are still at an early stage of development of the idea of local economic development, due to fact that the preparation of the municipal strategies and action plans are the only activities carried out in this direction so far.</p><p>The National Strategy for Agriculture and Rural Development for the period 2009-2013 stresses tourism and agriculture as priority areas for development of the country and analyzes the situation and the range of responsibilities of the Ministry of Agriculture, Forestry and Water Management. Parallel, the national programs facilitating agriculture and rural development in Macedonia in favor of global trends for creation of sustainability in rural regions through the development of agriculture and additional activities for families living or returning to rural areas (villages). The rural development through the few authentic examples in Macedonia already shows the first interest although the contours of the branch are not defined yet.</p>The rural development is able to a greater extent to meet the needs of the modern man that the urban environment is not able to satisfy. To clarify what can be these unmet needs and to answer the question of interest due to demand for this type of tourism, it is necessary to analyze contained rural tourism.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.288
Teacher spread0.255 · 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 designOther design
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

Citations0
Published2016
Admission routes1
Has abstractyes

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