An assessment of households’ perceptions of private security companies and crime in urban Ghana
Bibliographic record
Abstract
Amidst the growing incidence of urban crime in Ghana is the proliferation of private security companies (PSCs). As of December 2014, Ghana’s Ministry of Interior, responsible for the registration and regulation of PSCs, reported that there were as many as 176 licensed companies in ‘good standing’ (that is, companies which have renewed their operating licenses) in the country. In broad terms, the proliferation of PSCs reflects a global trend and represents a logical extension of economic liberalization and privatization efforts of the Ghanaian state. The broad proposition in the security literature is that as the state cuts back on public services such as policing and security, the popular doctrine of resilience shifts the burden of security to society and consequently justifying the use of private security organizations. While PSCs have proliferated in recent decades, little studies have been done regarding their conformity with the existing policy, institutional and legal framework that set them up and the public perceptions about their activities and crime prevention in Ghanaian cities. More importantly, the extent to which PSCs have impacted on crime incidence and the public’s perceptions on their operations and accessibility remain to be explored. Based on key informant interviews as well as a survey of 2745 households undertaken in key Ghanaian cities (Accra, Kumasi, Sekondi-Takoradi and Tamale), this study seeks to bridge these knowledge gaps by critically examining households’ perceptions of PSCs and crime in large Ghanaian metropolitan cities. Quite contrary to the dominant propositions in the literature, the household survey identifies job creation/business as the single most important driver for the proliferation of PSCs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".