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Record W4380520999 · doi:10.6000/1929-4409.2020.09.336

The Contribution of Social Entrepreneurship to the Development of Human Capital of Students

2022· article· en· W4380520999 on OpenAlexvenueno aff
Н.П. Клушина, В.В. Рощупкина, Sergey Kotov, Н. П. Петрова, Р. М. Абдулгалимов

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldComputer Science
TopicEducational Innovations and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsHuman capitalEntrepreneurshipSocial capitalCurriculumWork (physics)Modular designPhenomenonTask (project management)SociologyIndividual capitalPolitical scienceEconomic growthPublic relationsSocial scienceManagementEconomicsEconomic capitalPedagogyEngineeringComputer scienceLawEpistemology

Abstract

fetched live from OpenAlex

The article presents the author’s vision of the place and role of social entrepreneurship in the development of the human capital of students. The authors note that the ongoing changes in society and the economy pose the most important task - the study of a phenomenon such as human capital. Training in social entrepreneurship of students can somehow contribute to the formation of the individual human capital of a student to more successfully adapt to the modern labor market. The authors proposed a model of human capital consisting of seven components, which served as the basis for the development and implementation of a modular curriculum in the work of several universities. The article presents a pedagogical experiment on testing a modular program at universities in the South and North Caucasus Federal Districts and evaluates its results. Suggestions were made for the development of an urgent and state-important strategic direction for universities - a focus on the formation of positive human capital for students.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score0.170

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 science0.0010.000
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 head0.079
GPT teacher head0.376
Teacher spread0.297 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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