The relationship between college students’ extraversion and entrepreneurial intention: The mediating role of perceived social support
Bibliographic record
Abstract
Our study presents the connection between extraversion, entrepreneurial intention, and perceived social support among college students, and draws from entrepreneurial event models, career choice theory, resource dependence theory, and buffer theory. We aimed to construct a relationship model linking extraversion, perceived social support, and entrepreneurial intentions, focusing on perceived social support as a personal resource. We conducted a survey involving 1,133 college students, employing the Chinese Big Five Personality Inventory, Entrepreneurship Intention Vector Scale, and Perceived Social Support Scale. Notably, male students exhibited significantly higher entrepreneurial intentions than their female counterparts. Moreover, we found that perceived social support partially mediated the link between extraversion and entrepreneurial intentions in college students. In summary, extraversion directly influences entrepreneurial intentions, with perceived social support acting as a mediating factor within this relationship. This study sheds light on the interplay of personality traits and social support in shaping entrepreneurial intentions among college students.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".