FACTORS AFFECTING THE USE OF PUBLIC SUPPORT SERVICES BY SME OWNERS: EVIDENCE FROM A PERIPHERY REGION OF CANADA
Bibliographic record
Abstract
Public authorities throughout the world, recognizing both the importance and fragility of SMEs, have over the years created agencies and set up numerous venture development support and assistance measures. Despite all these efforts, SME owner-managers do not appear to make maximum use of the services available. Results from a survey of 70 SME owner-managers show that the likelihood of an SME using public support services increases as the perceived usefulness of public agencies and their services increases, and as the level of knowledge of public agencies increases. Furthermore, the probability of using public support services decreases as the experience of the owner-manager increases. On one hand, many owner-managers do not seem to understand the utility or relevance of the services the agencies provide, while on the other, they do not seem to know enough about the agencies working in their region. However, most of the owner-managers who had used the agencies felt the services they had received were appropriate to their needs. Therefore, the problem appears to lie more with the perceptions of certain owner-managers than with the nature or quality of the services themselves.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".