Australian small and medium sized enterprises (SMEs): A study of high performance management practices
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 While there is extensive management and academic literature on the topic area of high performance management internationally, research on high performance management practices in the Australian context is limited. Furthermore, research on high performance management practices has focused predominantly on large organisations and is largely a new direction for research in SMEs. This study attempts to fill some of the gaps in existing studies by considering a wide range of high performance management practices in Australian SMEs. Owing to the dearth of national data on high performance management in Australian SMEs, the results of this study are used to determine whether there is any evidence of a ‘high performing’ scenario in relation to management practices in Australian SMEs. The results, reporting a national study (N = 1435) on employee management in Australian SMEs, reveal a moderate take-up of high performance management practices. The findings by themselves do not support a ‘high’ performing scenario in relation to management practices in SMEs; however the low application of participative practices in the context of low unionization, and a low incidence of collective relations, indicates that many SMEs need a makeover if they are to meet the demands of competition. It is evident from the findings in this study that high performance practices in SMEs stand to benefit from modernisation and improvement.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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