#1 CAP Models – The Characteristics.

The research of Crime Action Profiling (CAP) is characterized by a set of distinct methodological procedures that have been used to develop models of crime behaviors and associated offender characteristics. The application of these models for profiling violent crimes can be achieved at a theoretically complex or simple, more practical level. The theoretical use of the CAP models predominantly involves an understanding of the methodological development of the models, the discernment of behavioral clusters, and the relevance they hold with previously proposed taxonomies of serial violent offenders. However, a less theoretically oriented application of the CAP models can also be achieved by those unfamiliar with complex statistical methodologies. Consequently, this chapter explains a set of generic principles whereby any of the CAP models can be interpreted for the purpose of developing a criminal profile without a detailed understanding of the methodologies inherent to the development of these models.

It should be noted that although the studies in the three subsequent chapters consider differing forms of violent crime, they all share the same methodological basis that characterizes the CAP approach to the profiling of these types of crimes. Consequently, the material that follows endeavors to provide a generic and easily comprehensible method by which a lay person unfamiliar with research methodologies and/or statistical procedures can nonetheless interpret the CAP models and apply them for the purpose of developing a criminal profile. At the outset it should be understood that MDS is not a method or technique for criminal profiling but merely a form of statistical analysis akin to other statistical measures, such as analysis of variance (ANOVA), for example. Additionally, it should be noted that MDS is not a statistic itself, but rather a type of statistical analysis. There are a number of different types of MDS that can be used to analyze different forms of data. Perhaps the best starting point in explaining MDS is to discuss the much simpler and somewhat similar statistical procedure of correlation. Imagine, for example, that one wishes to study the relationship, if any, between the sale of cold drinks and the daily temperature. In this hypothetical example we would be investigating the relationship, if any, between two variables: the number of drinks sold and the daily temperature. One method by which a scientist could investigate the relationship, if any, between these two variables would be to record the number of drinks sold over a number of days while also recording the corresponding temperature on each of those days.

A detailed understanding of the mathematical principles inherent to correlation is not necessary for the purposes of this discussion. Suffice to say that by incorporating the recorded data into a mathematical formula (which is the correlation statistic) some understanding of the relationship inherent to the data can be determined. The result of these calculations produces a number referred to in statistical parlance as a correlation coefficient. Depending on the size of this number as well as its polarity (i.e., whether the number is positive or negative), some understanding of the relationship between drink sales and temperature can be determined. Thus, in the hypothetical example the result of this statistical analysis provides a large positive number. In this circumstance we could conclude that a strongincremental relationship exists between the two variables. Interpreting this statistical result in the context of our example suggests that there is a tendency for drink sales to increase when the temperature rises. hotter the day, the more drinks that are sold. In some respects, MDS merely represents a more sophisticated form of correlation. That is, it is a statistical procedure that examines the relationships, if any, between variables. However, in explaining MDS there are two important features to bear in mind. First, in the previous example of correlation only two variables were considered, drink sales and temperature. MDS, however, is capable of simultaneously examining the relationships between numerous variables. The second important feature surrounding MDS is the method by which the results of the analysis concerning the relationships between variables are expressed. With correlation these relationships are communicated via the use of a number referred to as a correlation coefficient.

It is the position of the icon within this square, relative to the position of any other icons (representing other variables) within the square that illustrates the relationship between the variables. Consequently, two icons representing two variables plotted on a MDS diagram in close proximity to each other indicates that these two variables hold a close or strong relationship to one another. A third icon located in a remote region of the square diagram relative to the position of the first two icons denotes that this third variable does not hold a strong, or possibly any relationship, with the first two. Conversely, icons located in the outlying regions of the square are more distinct and do not share many common relationships with the exception of other variables that may also be located in the same outlying region. Imagine that a scientist wishes to study the differing types of motor vehicles. The first step in such a study would involve the development of a list of possible components found in motor vehicles. For the sake of simplicity, the list in this example will merely comprise of tires, carbon fiber chassis, steel chassis, steering wheel, and handlebars. Each of these items represents a separate variable in the scientist’s study of motor vehicles. With this list of variables determined, a sample of motor vehicles would then need to be collected. Each of these vehicles would be examined to see which of the five variables on the list each particular vehicle featured. data for the scientist’s study. Given the mathematical complexity of MDS, most contemporary applications are achieved by using computer programs that perform the multitude of calculations inherent to this analysis and plot the results in the form of a diagram. Consequently, the data collected from our sample of motor vehicles would typically be entered into a computer program, which would then perform the analysis and generate a diagram representative of this analysis. MDS only analyzes and allows for the identification of patterns in the studied crime behaviors. In effect, therefore, these MDS analyses only represent half of the profiling process in that it provides a method for interpreting crime behaviors. The other half of the process of criminal profiling involves discerning how any behavior patterns displayed in the MDS diagrams are related to offender characteristics.

In conclusion, although the statistical procedures involved in developing the various CAP models are admittedly a little complex, the process of interpreting the models and thus understanding the relationships between crime behaviors and offender characteristics is relatively straightforward. Various arrows display a collection of offender characteristics.

Acknowledgements:

The Police Department; 

www.politie.nl and a Chief Inspector – Mr. Erik Akerboom    ©

Bibliography:

1.    Criminal Investigations – Crime Scene Investigation.2000

2.    Forensic Science.2006

3.    Techniques of Crime Scene Investigation.2012

4.    Forensics Pathology.2001

5.    Pathology.2005 

6.    Forensic DNA Technology (Lewis Publishers,New York, 1991).

7.    The Examination and Typing of Bloodstains in the Crime Laboratory (U.S. Department of Justice, Washington, D.C., 1971).

8.    „A Short History of the Polymerase Chain Reaction". PCR Protocols. Methods in Molecular Biology.

9.    Molecular Cloning: A Laboratory Manual (3rd ed.). Cold Spring Harbor,N.Y.: Cold Spring Harbor Laboratory Press.2001

10.   "Antibodies as Thermolabile Switches: High Temperature Triggering for the Polymerase Chain Reaction". Bio/Technology.1994

11.   Forensic Science Handbook, vol. III (Regents/Prentice Hall, Englewood Cliffs, NJ, 1993).

12.   "Thermostable DNA Polymerases for a Wide Spectrum of Applications: Comparison of a Robust Hybrid TopoTaq to other enzymes". In Kieleczawa J. DNA Sequencing II: Optimizing Preparation and Cleanup. Jones and Bartlett. 2006

13.   Nielsen B, et al., Acute and adaptive responses in humans to exercise in a warm, humid environment, Eur J Physiol 1997

14.   Molnar GW, Survival of hypothermia by men immersed in the ocean. JAMA 1946

15.   Paton BC, Accidental hypothermia. Pharmacol Ther 1983

16.   Simpson K, Exposure to cold-starvation and neglect, in Simpson K (Ed): Modem Trends in Forensic Medicine. St Louis, MO, Mosby Co, 1953.

17.   Fitzgerald FT, Hypoglycemia and accidental hypothermia in an alcoholic population. West J Med 1980

18.   Stoner HB et al., Metabolic aspects of hypothermia in the elderly. Clin Sci 1980

19.   MacGregor DC et al., The effects of ether, ethanol, propanol and butanol on tolerance to deep hypothermia. Dis Chest 1966

20.   Cooper KE, Hunter AR, and Keatinge WR, Accidental hypothermia. Int Anesthesia Clin 1964

21.   Keatinge WR. The effects of subcutaneous fat and of previous exposure to cold on the body temperature, peripheral blood flow and metabolic rate of men in cold water. J Physiol 1960

22.   Sloan REG and Keatinge WR, Cooling rates of young people swimming in cold water. J Appl Physiol 1973

23.   Keatinge WR, Role of cold and immersion accidents. In Adam JM (Ed) Hypothermia – Ashore and Afloat. 1981, Chapter 4, Aberdeen Univ. Press, GB.

24.   Keatinge WR and Evans M, The respiratory and cardiovascular responses to immersion in cold and warm water. QJ Exp Physiol 1961

25.   Keatinge WR and Nadel JA, Immediate respiratory response to sudden cooling of the skin. J Appl Physiol 1965

26.   Golden F. St C. and Hurvey GR, The “After Drop” and death after rescue from immersion in cold water. In Adam JM (Ed). Hypothermia – Ashore and Afloat, Chapter 5, Aberdeen Univ. Press, GB 1981.

27.   Burton AC and Bazett HC, Study of average temperature of tissue, of exchange of heat and vasomotor responses in man by means of bath coloremeter. Am J Physiol 1936

28.   Adam JM, Cold Weather: Its characteristics, dangers and assessment, In Adam JM (Ed).Hypothermia – Ashore and Afloat, Aberdeen Univ. Press, GB1981.

29.   Modell JH and Davis JH, Electrolyte changes in human drowning victims.Anesthesiology 1969

30.   Bolte RG, et al., The use of extracorporeal rewarming in a child submerged for 66 minutes. JAMA 1988

31.   Ornato JP, The resuscitation of near-drowning victims. JAMA 1986

32.   Conn AW and Barker CA: Fresh water drowning and near-drowning — An update.1984;

33.   Reh H, On the early postmortem course of “washerwoman’s skin at the fingertips.” Z Rechtsmed 1984;

34.   Gonzales TA, Vance M, Helpern M, Legal Medicine and Toxicology. New York, Appleton-Century Co, 1937.

35.   Peabody AJ, Diatoms and drowning – A review, Med Sci Law 1980

36.   Foged N, Diatoms and drowning — Once more.Forens Sci Int 1983

37.   "Microscale chaotic advection enables robust convective DNA replication.". Analytical Chemistry. 2013

38.   Sourcebook in Forensic Serology, Immunology, and Biochemistry (U.S. Department of Justice, National Institute of Justice, Washington, D.C.,1983).

39.   C. A. Villee et al., Biology (Saunders College Publishing, Philadelphia, 2nd ed.,1989).

40.   Molecular Biology of the Gene (Benjamin/Cummings Publishing Company, Menlo Park, CA, 4th ed., 1987).

41.   Molecular Evolutionary Genetics (Plenum Press, New York,1985).

42.   Human Physiology. An Integrate. 2016

43.   Dumas JL and Walker N, Bilateral scapular fractures secondary to electrical shock. Arch. Orthopaed & Trauma Surg, 1992; 111(5)

44.   Stueland DT, et al., Bilateral humeral fractures from electrically induced muscular spasm. J. of Emerg. Med. 1989

45.   Shaheen MA and Sabet NA, Bilateral simultaneous fracture of the femoral neck following electrical shock. Injury. 1984

46.   Rajam KH, et al., Fracture of vertebral bodies caused by accidental electric shock. J. Indian Med Assoc. 1976

47.   Wright RK, Broisz HG, and Shuman M, The investigation of electrical injuries and deaths. Presented at the meeting of the American Academy of Forensic Science, Reno, NV, February 2000.