Perceived Benefits and Challenges of Management Graduates of Far Western University towards the Entrepreneurship Intention
Bibliographic record
Abstract
Entrepreneurs are contributing a lot for the economic and social development of each country of world. The aim of this study is to explore perceived benefits and challenges of management graduates of Far Western University towards the entrepreneurial intention. Data were collected from 107 students who are currently studying M.Phil., MBA and MBS in central campus Far Western University. A set of questionnaires was designed as the main instrument of data collection which consist the 17 questions related to perceived strength, weakness, opportunities and threats (SWOT) of the respondents. Out of the 17 questions, first four are related to the opportunities, second five are related to challenges, third four are related to strength and last four are related to weakness. The instrument for data collection comprised of 6-point Likert type scale. To explore the perceived benefits and challenges of entrepreneurship intentions of management graduates of Far Western university descriptive statistics has been used. Data were processed by using computer software SPSS. The result indicates that ongoing rapid urbanization has perceived a great opportunity or highly motivates the students to start up business and financial problem is perceived as main obstacles to be an entrepreneur.
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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 | 0.002 |
| 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".