Policing for the people

Abstract

PurposeThe UK police service has a major challenge to introduce innovative ways of improving efficiency and productivity, whilst at the same time improving public opinion as to their effectiveness in the “fight against crime”. The purpose of this paper is to outline an exploratory study of the ability to cluster police forces based on their sanction detection levels over a number of different offence groups and whether these clusters have different associated public opinions towards them.Design/methodology/approachUsing secondary data and the fuzzy c‐means clustering technique to exposit clusters of police forces based on sanction detection levels, relating them in a statistical analysis with public opinion on the police.FindingsThe clustering analysis shows how police forces can be considered relative to each other, based on their sanction detection levels of certain offence groups, including; burglary, fraud and forgery and criminal damage. Using the established clusters of police forces, in respect of independent variables relating to public opinion, including confidence in police; there does appear to be statistically significant differences amongst the clusters of police force.Research limitations/implicationsThe results demonstrate the connection between the police's attempt to fight crime and public opinion. With the public opinion measures considered post the establishing of police forces’ clusters, the results show the public does notice the level of sanction detections achieved. The identified disconnect of the public with the criminal justice system is something that can be improved on in the future.Practical implicationsDemonstrates that there is a significant link in the relationship between the levels of sanction detection levels of police forces and public opinion about their ability to fight crime.Originality/valueThis paper employs fuzzy c‐means, a modern clustering technique nascent in this area of research.