Training women to win: women and enterprise development in the UK
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Within the SME sector, women are responsible for about one third of all start-up businesses in the UK. They are vital to the economy and future growth of the SME sector. Their dynamism and enterprise enriches the sector. Despite the positive contribution and untapped potential of women in business, it appears that women may need help in seeing themselves as entrepreneurs and as leaders, and in enhancing their personal skills and the viability, growth potential, and sustainability of their businesses. The key question is: Do they get the help they need? If not, why not, and what, if anything, needs to change? This article sets out to look at these issues. It seeks to identify current good practice in terms of available support and to produce and pilot recommendations that will improve current business support and training provision for women. For academics, this article adds to the growing literature on female entrepreneurship. For business support professionals and policy makers, this article provides recommendations for use when supporting future initiatives and produces recommendations highlighting the possible direction of future provision. INTRODUCTION The number of women business owners is growing around the world; 1 in 11 women worldwide is now an entrepreneur (GEM, 2004). In the UK, women comprise 27% of selfemployed and own-account workers, compared with 34% in Austria, 28.7% in Belgium, 33.4% in Canada, 32.3% in Finland, and 39.8% in Portugal. In the U.S., around 30% of businesses are wholly or majority owned by women; in the UK, this number is 14%. Men are twice as likely to be entrepreneurs in the UK as women are. The British government has expressed a desire to have more women in business and has set targets to achieve this. The 2007 Global Entrepreneurship Monitor showed a growth in total entrepreneurial activity in the UK; however, women are still around half as likely to be involved in business start-up activity as men. In 2005, 3.74% of the female adult population were involved in independent start-up activity, compared to 6.17% of the male population (Minniti, Bygrave, & Autio, 2006). This article sets out to investigate training and business support provision for women, to see whether it has been effective, and to assess the impact of targeted women's enterprise support. This is based on an original report, Training Women to Win (Dhaliwal, Combly, Cundell, Lock, & Thomas, 2006), at the University of Surrey. The findings here will be applicable to women business owners in other countries, developing and developed, who can draw on the lessons and experiences of UK women in business. The structure of the paper is straightforward. The next section is a literature review drawing out the main issues pertinent to this article, followed by the methodology, report on findings, and conclusions and recommendations. LITERATURE REVIEW Early studies on female entrepreneurs concentrated on descriptive accounts of the characteristics and motivations of women in business and their experiences of business ownership, particularly at start up. More sophisticated studies include themes on gender differences regarding management of the business, particularly with regard to finance, business networks, and performance (Carter & Anderson, 2001; Carter, Anderson, & Shaw, 2001). Several studies have compared the performance of men and women in business. Findings for the Caribbean (Finnegan, 2003) and for Asian women (Dhaliwal, 1998) found that women are less likely to be members of associations than men. There are some issues that affect many women setting up their own businesses in specific ways, and some women find it difficult to achieve their full business potential in an environment that has been designed for a different model of entrepreneur (Carter & Shaw, 2006). Mirchandani (1999) challenges these comparative studies, as they do not illuminate how and why entrepreneurship came to be defined and understood vis-avis the behavior of only men. …
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it