Published by Canadian Center of Science and Education 245 Business Advisory: A Study on Selected Micro-sized SMEs in
Bibliographic record
Abstract
This study seeks to investigate the business advisory awareness among some micro-sized SMEs in Kelantan, Malaysia, focusing on the advisory services supplied by various government agencies. Micro-sized SMEs were the centre of the study because they represent a large number of SMEs in the country. Notwithstanding with the various advisory services provided by the government agencies in the state, result of the study showed the majority of respondents was not fully aware of and assured on the existence of business advisory services. Furthermore, the results of the study indicated no significant relationship between all the demographic factors of businesses and the level of awareness of business advisory among micro-sized SMEs. The key findings of the study are instructive. Actions should be taken by the government and its relevant agencies to enhance the level of awareness and knowledge of the importance of advisory among micro-sized SMEs. It seemed that the information pertaining to the business advisory services are not well disseminated to the targeted group. This failure distorts the government plan to efficiently support SMEs, thus leading to waste of scarce resources. Suggestions were also made to significantly address these issues.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.304 | 0.055 |
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".