Discouraged Advisees? The Influence of Gender, Ethnicity, and Education in the Use of Advice and Finance by UK SMEs
Bibliographic record
Abstract
We investigate the influence of gender, ethnicity, and education in the use of external advice and finance by UK small and medium-sized enterprises (SMEs). A conceptual model of ‘discouraged advisees’ was developed as a framework for analysis of the results of a telephone survey of 400 SMEs. We found an association between the use of external advice and the ability to raise bank finance. Furthermore, both men and black and minority ethnic (BME) participants were more likely to use family and friends for advice, whilst women were twice as likely as men to use Business Link. BME business owners were discouraged from using less ‘trusted’ sources, such as Business Link, possibly believing them insufficiently tailored or that they would provide inappropriate advice. Therefore, the findings provide support for our conceptual model of discouraged advisees and have implications for the provision of advice for business owners from BME communities.
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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 | 0.000 |
| 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".