New directions in the management of human resources in Africa
Bibliographic record
Abstract
The last decade has witnessed a notable increase in the volume of publications on human resource management (HRM) in Africa, particularly in reputable management journals. Yet, within the broader context of the mainstream HRM debate, advances in research and theoretical sophistication have not quite kept pace with the actual practice of management. This is particularly notable when it comes to the progress that organizations in Africa have made in product innovation and service delivery, the creation and application of advanced technology, as well as in the adoption of progressive/innovative HRM practices. The six papers in this forum were drawn from an international conference on HRM in Africa held at Nottingham Business School in 2010. Taken together, they identify important new developments in theory and practice, and also open up avenues for further debate particularly in the areas of career development, knowledge appropriation, mergers and acquisitions, the role of HR professionals, the informal sector and the most effective ways to engage foreign investors.
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.
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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".