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Record W2147293957 · doi:10.5430/bmr.v3n2p18

Facilitating Elements for the Transmission of the Entrepreneurial Spirit in the Classroom

2014· article· en· W2147293957 on OpenAlexvenueno aff
José Manuel Comeche, Jose Vicente Pascual

Bibliographic record

VenueBusiness and Management Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityEntrepreneurshipContext (archaeology)Vocational educationPsychologyEntrepreneurial spiritClass (philosophy)SociologyIdeationMathematics educationMarketingPedagogyComputer scienceBusinessSocial psychologyCognitive scienceArtificial intelligence

Abstract

fetched live from OpenAlex

There have been countless tests made to confirm that creativity is a critical skill for entrepreneurs and their entrepreneurial training (Schmidt, J. et al. 2012), even more, practices on divergent thinking increases the entrepreneurial skills of students to generate a greater number and range of ideas, but not, their approaches to solve problems in a creative way. This situation raises a number of questions that should be analyzed before adding creativity and techniques to improve the training of creative thinking to studies (classes), about and in entrepreneurship, as a training channel, improvement or even to the generation of entrepreneurs. Our goal is to show that entrepreneurship is a facet of creativity and that the "hidden" entrepreneur in the learner, will need to observe and confirm the existence of sufficient external constraints -context and social network- to release its entrepreneurial attitude, furthermore it will be essential, that teachers adopt an innovative approach that enables a suitable context, in this way almost intuitively, and vocational - show student behaviors associated with entrepreneurial attitudes. In our work, we found out that the implementation of an innovative teaching contributes to facilitate the transmission of the entrepreneurial spirit and improves the use of gen-preneur in class.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.054
GPT teacher head0.314
Teacher spread0.260 · 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 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

Citations5
Published2014
Admission routes1
Has abstractyes

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