Small- and Medium-Sized Enterprise Finance Monitor, 2011-2017
Bibliographic record
Abstract
The Small- and Medium-Sized Enterprise Finance Monitor survey is commissioned by the Business Finance Taskforce to provide an independent and authoritative report into the key issues of SME Finance. 4,500 telephone interviews are conducted per quarter (5,000 interviews prior to 2016), across the UK, to a carefully structured sample of SMEs by size, sector and region. Data for Q4 2017 was collected between October and December 2017. The data set includes all data collected for the last 10 waves, i.e. from Q3 2015 until Q4 2017, whilst the report focuses on data gathered from the last 4 quarters. The report is now released biannually; the latest report is submitted now for Q4 2017, and the next one will follow after Q2 2018. The survey explores demand for external funding amongst SMEs and the response to requests for funding made to banks in the last 12 months. It also asks for future finance needs and assesses business confidence, growth, and barriers to growth for the future, as well as the impact of a lending experience on the overall banking relationship. As well as identifying the proportion of SMEs that have approached a lender for external finance, the survey identified those who would have liked to apply, but haven't, the barriers to such an application, and the impact of the decision not to seek funding on business performance. A wide range of business demographics are collected to allow for sub-group analysis by criertia such as age of business, external risk rating, type of facility requested, and the “formality” of the business (planning, HR policies, importing, exporting, etc.). The intention is for this to become the definitive data set on this topic for banks, government, business organisations and other interested parties, including academics. It is hoped it will be used to provide answers, to obviate the need for similar quantitative research, and to provide the starting point for spin off projects into specific aspects of SME Finance. Further information is available on the SME Finance Monitor web page. Latest Edition Information For the 19th edition (May 2018) additional data and documentation were deposited to extend the coverage to Quarter 4, 2017.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.011 |
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".