Police - Driver Interaction and Traffic Law Enforcement in Madina and Adenta-Ghana

Abstract

Road traffic accidents and fatalities are a serious concern globally due to its negative implications on health, social and economic wellbeing of the people. This preventable phenomenon is wiping away millions of lives and also depleting economic resources of countries especially developing countries who own 48% only of the world‘s vehicles yet account for 90% of all road accidents and fatalities in the world. Several attempts such as legislation, engineering and technological improvement of cars have yielded minimal gains. The solution seems to be with rigorous traffic law enforcement. In Ghana this interaction between the main actors in the traffic law enforcement is actively taking place yet the impact has been oblivious. Therefore, the main thrust of the study has been to explore nature of interaction between the main actors and to ascertain the impact of the alleged police corruptibility on traffic law enforcement in Madina and Adenta. Using the mixed method approach and drawing from the theories of social encounter and differential association, the study relies on observation, interviews and survey to obtain data from 60 police officers and 120 drivers. The findings strongly suggest that drivers and the Police viewed the interaction between them as cordial and hostile respectively. The data also showed that the police is corruptible and extort monies from drivers in their official duties. This result gives credence to the outcome of the hypothesis that there is a significant relationship between bribe giving and the likelihood of drivers not to adhere to traffic regulations. The results of the second hypothesis tested, revealed significant relationship between being conversant with traffic laws and the propensity to violate it. The study recommended that enforcement activities should be designed to maximise deterrence effects, encourage the Police to undertake highly visible enforcement operations and also introduce automated red light cameras and turning lanes at high accident risk intersections.