Developing student’s social entrepreneurial intention
Bibliographic record
Abstract
The purpose of this study is to analyze the effect of emotional intelligence, experience of social experience, previous entrepreneurial experience, environmental support toward social entrepreneurial intention with mediating role of social entrepreneurial self-efficacy.Research sample consisted of 125 students who has some social experience and entrepreneurship from various universities in Semarang.The data carried out in 2019 and analyzed with a Structural Equation Modeling (SEM) using AMOS v 21.The results show that emotional intelligence, social activities, previous entrepreneurial experience were significantly and positively associated with social entrepreneurial, self-efficacy and social entrepreneurial intention.Social entrepreneurial self-efficacy significantly and positively influenced on social entrepreneurial intention.However, the effects of environmental support on social entrepreneurial intention was insignificant.The significant mediating role of student's social entrepreneurial self-efficacy in developing social entrepreneurial intention showed significant contribution of social cognitive theory and career development theory to realize student's social entrepreneurial intention.University and government are requested to give more attention in developing social entrepreneurship in order to have more social entrepreneur graduated from universities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".