An Analysis of Public Order Policing in the Gauteng Province, South Africa
Bibliographic record
Abstract
Background: Public order policing (POP) has attracted considerable interest from the academic community due to public protests in South Africa. This is not surprising given that it represents an important component of police work. As South Africa’s democracy has been maturing, the democratic dispensation brought the promise of civil liberties and a human rights culture. Although these parallel developments brought prospects of accountability and legitimacy by the South African Police Service (SAPS), the restoration of public order, especially during public protests, has remained a challenge for the SAPS. Purpose: The objectives of this research were threefold: to explore the role of the POP unit; to explore its capacity to respond to public protests; and to determine the effectiveness of the integrated interventions of the relevant stakeholders to restore engagement and order. Methods: A qualitative research approach employing semi-structured interviews was utilised. To understand the policing of public protests, purposeful sampling was utilised to select 25 participants comprising community members, municipal officials, and POP members. These participants were selected since they are directly involved either in responding to public order or being part of protests, and it was therefore envisaged that their contribution would assist in understanding how protests are responded to. Conclusion: The findings indicate that when the POP units that are mandated to fulfil these goals are not effective, disruptions of public order are minimised and the destructive consequences of those that do occur are contained. The results illustrate that the restoration of public order necessitates regenerating public order characterised by low expectations of violence and a heightened respect for human rights. Recommendations: This article recommends that the relevant stakeholders in collaboration with the POP unit must respond adequately to the maintenance of safety and security during protests. The relevant stakeholders and the POP unit should enhance the effectiveness of the current strategies to be able to deal with anticipated public violence and disorder, improvement of the intelligence-gathering process to plan properly, adequate and proper training facilities, reviewing and updating of training manuals, and methods based on lessons learned and best practices to ensure that the training is relevant. POP members must undergo regular training and in-service training to maintain their fitness levels, standards, proficiency, and competencies.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".