The roles of learning orientation and passion for work in the formation of entrepreneurial intention
Bibliographic record
Abstract
In order to extend understanding of the drivers that underlie entrepreneurial intention formation, this article investigates the hitherto underexplored roles of people’s learning orientation and passion for work. It considers how these personal characteristics may moderate the instrumentality of their perceived ability to become a successful entrepreneur, and perceptions of the attractiveness of becoming an entrepreneur. Using a survey of 946 university students, it finds that learning orientation and passion for work invigorate the role of these feasibility and desirability considerations in enhancing entrepreneurial intention. A follow-up analysis reveals that the moderating effects of learning orientation and passion for work on the perceived attractiveness–entrepreneurial intention relationship are stronger to the extent that people value the intrinsic goal of autonomy in their future career more, but these moderating effects are immune to the importance of the extrinsic goal of earning financial rewards. Several implications for research and practice emerge.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".