Evaluation

• The top-down approach assumes that criminals have free will, which means they can choose whether or not to engage in criminal behavior.
• Top-down approach


  • Useful for police in directing resources and understanding offender characteristics
  • Limited to certain crimes like murders, rapes, arsons
  • Not useful for more common crimes like burglary and property destruction
• Top-down profiling can only be used for a limited range of crimes
• More common offences such as burglary and destruction of property do not lend themselves to profiling because the resulting crime scene reveals very little about the offender
• The top-down approach is a limited approach to identifying a criminal of only certain crimes
• Problem with top-down approach research

  • Researchers only focus on one variable that could be the cause of an offender committing a crime
  • Some offenders could show characteristics of both organised and disorganised typologies
• Content analysis on 100 cases of serial killers in the US found no clear distinction between organised and disorganised crimes
• The criteria for identifying disorganised and organised crimes are too simplistic
• Other factors such as individual personality differences between offenders need to be considered
• Criticism of top-down approach

  • Problem of generalising the results to offenders of different crimes, locations, races, or genders
  • The original data is based on interviews with 36 of the most dangerous and sexually motivated murderers, which is not representative of all offenders
• The top-down approach is not based in any science or theory
• The accuracy of the profiles generated might be very subjective and open to interpretation
• The Barnum Effect whereby vague evidence of the crime could be manipulated to fit into the characteristics of a particular type of offender
• Profiling has the potential to cause harm if the profiles are wrong and mislead investigations
• The bottom-up approach is considered more scientific as it is based on objective statistical techniques and computer analysis