An Analysis of Criminology as a Profession in the Republic of South Africa
Bibliographic record
Abstract
The professionalisation of criminology has not been a smooth process in South Africa. The literature reveals that it has been a slow process burdened with numerous challenges. The slow process of professionalising criminology has caused uncertainty about criminology as a profession. Although, South African universities have taken the significant steps towards recognising criminology as an academic discipline. This systematic review studied various sources to justify the inability of relevant structures to professionalise criminology. Moreover, it endeavoured to understand the extent to which criminology has been professionalised in South Africa. This critical analysis confirms that the process of professionalising criminology has been prolonged and that it has been fraught with challenges. Results of this study are relevant for any idea to restructure the criminology, and it is envisaged that appropriate structures may find results useful in altering the vision of the profession. This paper recommends that an independent professional board be established to assist and guide criminologists. Such a board could, for instance, suggest a constructive structure and broadly define the role and functions of criminologists within the South African context.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.016 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".