The Evaluation of Leadership Development at a State Owned Enterprise in South Africa
Bibliographic record
Abstract
The study was sparked by concerns in the Human Resources Department at Denel, a State Owned Company/Enterprise in South Africa, regarding the state of leadership in the organization. The concerns were primarily that the leadership style in general, was ‘command and control’ - autocratic, bureaucratic and lacking the necessary commercial mindset and emotional intelligence needed to deal with employees from a motivational and employee-engagement perspective. The purpose of the research was to conduct an investigation into leadership at Denel and to analyse the perceptions, opinions and concerns of all stakeholders in the company. A qualitative research methodology was used and the findings confirmed that leadership styles at Denel were indeed traditional command and control, autocratic, lacked a commercial mindset and lacked emotional intelligence. Furthermore, the existing repertoire of leadership development programmes lacked work-based application relevance and the leadership development approaches were haphazard, with no proper focus and direction. Furthermore, there was no measurement of the impact of the leadership development interventions in the company to determine the return on investment. The recommendation is that leaders at Denel should create a culture of talent optimization, be transformed into business leaders and ensure employee motivation and engagement levels are enhanced within the company.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".