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Record W7082458832

Сравнительный анализ международного опыта реализации социально-инновационных проектов

2020· article· en· W7082458832 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic scientific archive of UrFU (Ural Federal University) · 2020
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsInefficiencyValue (mathematics)Social innovationIrrational numberSocial transformationSocial changeKnowledge base
DOInot available

Abstract

fetched live from OpenAlex

The rapid growth of social problems in society caused by the irrational use of resources, inefficiency of existing institutions, and transformation of value orientations has led to the search for new solutions in this area based on the analysis of international experience. The purpose of this study is to compare and identify the features of the formation of social innovation in international practice, particularly, in Canada, China, Spain and Italy. The article analyzes social innovation projects in the countries under review. The following criteria have been used for comparison: a customer, an innovator, his/her goal, the form of project implementation, and the source of funding. The methodological base of the research includes methods of systematization and comparative analysis. The scientific articles published in Web of Science, Scopus, E-library, international reports and statistics are base of research. Based on the analysis, the authors formulate the features of the formation of social and innovative activities in international practice and show the possibility of applying this experience in the Russian economy. The theoretical significance of the results obtained consists in the development of the theory of social innovations. Its practical significance lies in the possibility of using this experience for the development of social and innovative projects in the Russian economy.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.001
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 head0.012
GPT teacher head0.175
Teacher spread0.163 · 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 designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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Same venueElectronic scientific archive of UrFU (Ural Federal University)Same topicGeochemistry and Geologic MappingFrench-language works237,207