Identifying of Intrapreneurship Behaviors: Case of Country in Transition Economy
Bibliographic record
Abstract
Successful companies figure out that the most important elements in the organization are the ability to use the creativity of managers and employees through the recognition of their behaviors. One of the most important strategies for developing intrapreneurship in organizations is to improve and enhance the intrapreneurial behavior of employees, but what is deduced from the review of the history of the research is that most of the studies in the field of personality of entrepreneurs pointed to their characteristics and the type of properties is fewer studies, especially in developing countries and transition economies. The research is part of a series of research that seeks to identify and explore the components of intrapreneurial behavior in the organizations of Iran as a developing country, which is one of the economies in transition. This research is qualitative research in which a thematic analysis approach has been used. The statistical population of this project is selected among 170 competent firms. The findings of the study showed that 27 components of intrapreneurial behaviors in the organization, including 10 personality-based intrapreneurial behaviors and 17 effective entrepreneurial behaviors affected by the environment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".