Economic Empowerment of Malaysian Women through Entrepreneurship: Barriers and Enablers
Bibliographic record
Abstract
<p>The main aim of this study is to identify the barriers and enablers to Malaysian women’s entrepreneurship. A mixed method was used in this study. A qualitative approach using Delphi technique was used to obtain consensus on the barriers and enablers. This was incorporated into a questionnaire which was used in the survey of women entrepreneurs to obtain quantitative data on the barriers and enablers to women’s entrepreneurship. The respondents were 130 participants of a seminar for women entrepreneurs conducted by the Women’s Development Department of the Ministry of Women, Family and Community. The study found that the three top barriers were the lack of KSAOs followed by restrictive legalities, regulations and procedures and lack of business support and network. Personality and self-efficacy emerged as the most important enabler followed by support for businesses from government and women focused initiatives from government and NGOs.<strong></strong></p>
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".