Outline and Assess the Usefulness of Official Statistics of Crime to Sociologists.

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Outline and assess the usefulness of official statistics of crime to sociologists.

There are three main sources of information about the crimes for sociologists – the official crime statistics, which are collected by the police and are presented as secondary data for sociologists; victim survey such as British Crime Survey, which is also collected by the police and sponsored by the government, and in order to collect primary data sociologists use self-report studies and its aim is to uncover the true amount of crime in the society. OCS are a source of secondary data, therefore it can be trusted as it has been verified before by other researches and are accepted by some sociologists uncritically, for example functionalist sociologists explain why the youth and working class are more criminal just due to the fact that the OCS say so. As a result, Marxists argue that the OCS are being manipulated by the government that represents the ruling class in order to maintain their position and prevent the proletariat from gaining some power. There is a process called ‘cuffing’, which is when the police does not record the crimes that they cannot solve, that reduces the validity of the OCS as well as the fact these statistics are open to political abuse, therefore both positivists, who prefer quantitative data collected in a systematic way, and interpretivists, who seek for more in depth researches with a lot of qualitative data to find out the reasons, have all the rights to ignore this statistic as the dark figure of unrecorded statistics is still hidden, as the British Crime survey discovered that more crimes are found through research other than through reporting to police. Even though the statistics may be biased toward the government, the positivist would still argue that these statistics are highly reliable as they are collected in a scientific and systematic way, therefore they will be able to extrapolate and compare different trends and pattern, whereas...
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