An investigation into the effectiveness of public entities’ procurement 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
The delivery of services through the procurement of goods and services requires proper strategic leadership and management processes. Inappropriate planning, under-spending of budgets and ineffective procurement form part of the root causes of poor service delivery, as this restricts the movement of resources to the right places. This study identified the leading procurement practices as: procurement strategy and leadership, the procurement process, human resource management, procurement information systems, supplier management and procurement performance management. These practices were then tested in public entities, mainly in Gauteng Province, South Africa, to determine the extent to which they are applied. The study found that there is a major divide between the perception of the level of application of the leading practices and actual implementation. Processes, skills, performance management, information technology (IT) systems and supplier management are applied inadequately or inappropriately. Most entities thus show a poor understanding of customer needs and there seems to be a general lack of customer focus. The study highlighted the best practice areas in which public entities are able to focus their efforts to better achieve excellent customer service and thus service delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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