Creating crime scene action scales Manne Laukkanen P.S. Places marked in red are especially meant for discussion at the seminar

Current status of research field Police has at it’s use models of spatial behaviour of criminals in different types of crimes. (e.g. Santtila & al. 2004). That is, there are statistical depictions of journeys-to-crime giving information of how far from home offenders travel to offend. All of the crimes studied display a phenomenon called distance decay. Trips further away from residence of the offender are a minority. Data from 1992 to 2001 for a certain crime type serial criminal journeys to crime. Frequencies and kernel density estimation presented in graph. (Also normal distribution plotted for points sake)

This information of modelled traveling of offenders can be used to predict offender home location, when only the crime locations are known to the police. By using a continuous journey-to-crime -model created from empirical data for crimes or crime-series, it is possible to create a probability density surface that depicts the accumulation of probability in different parts of a particular study area. High probability areas may be prioritised by the police when conducting a criminal investigation. This approach is related to a sub-branch of criminal profiling (i.e. Canter & al. 2002) called geographic profiling (Rossmo 2002). The general aim of criminal profiling is to give a chance to prioritize suspects when they are numerous. It is of most use when dealing with serial criminals, although it can be used in single-crime investigations as well. This approach, however, is strictly statistical – it is only a generalization of the typical journey-to-crime behaviour of criminals in solved past crime incidents.

Background for setting of study - serial commercial robberies as data It is of interest to the police to enhance the accuracy of prediction of criminal home location with aforementioned method. It has already been discovered that some crime-scene action or crime- incident related variables correlate with distance the offenders travel from home to crime scene. –Choice of weapon – offenders with firearms often from further away  + correlation with distance. –Target – offenders robbing a bank (as opposed to a R-kiosk) from further away  correlation with distance. –Amount of preparation and/or professionalism Amount of disguise Escape vehicle or not....you guess the correlation.....generally, the more impulsive the crime or the criminal, the shorter the distance. In addition of being a strong common sense notion, this has received strong support in research. It is in the interest of the researcher to investigate, whether creating sub journey-to-crime -models for criminals behaving differently might enhance the accuracy of the prediction. That is, we would model the journey-to-crime behaviour anew for criminal sub-groups like ”the impulsives” vs. ”the professionals” (which may of course be opposite ends of one scale...)

Yes, we are aware that......these are solved crimes by criminals with a reported address. There are also people with no steady address, however, this is not so common in Finland. (Sleep outside – freeze to death)....the aforementioned blocks correlate sometimes very strongly (e.g. stimulus-reaction, no reaction without stimulus...)...because the perpetrators are sometimes parts of series of other perpetrators, the series are not ”clean”. (But this is how they are in reality...)...it is one challenge to recognize which deeds are parts of the same series. This is another field of study, we assume, that at the point we are requested a geographical profile, the police is certain the crimes presented form a series. There are methods for this....and several other things I will mention at the seminar.

The aim (for the needs of this seminar) To create a model that would enable us to separate a ”short traveller” from a ”long traveller” by analysing crime-scene behaviour. This requires finding themes from crime scene behaviour that: –form meaningful wholes from variables that are available for the police at start of investigation –are connected to distance

Methods considered MDS – themes correlation to distance. MDS dubbed too artistic by me. Dissed. Mokken scaling – meant for dichotomous variables, new and sexy, but I am not fluent in it’s theory. Dissed. Correlations of individual variables to distance – regression analyzing these – forming a regression model with regression loading scores. Will this form a sensible scale? Ease of use by the police? Psychologically boring, but probably ok otherwise. Possibility. Factor analysis, checking the correlation of different factors to distance. Psychologically most interesting, as this would use the connection of crime-scene behaviour style and distance in a psychological and not just statistical way. Possibility.

The measurement model As it became apparent that trying to use ordered variable values was often surprisingly unrealistic and caused unexpected results, it was decided to use dichotomous variables for crime scene behaviour  variable present – variable not present. –For example, the danger presented to the staff by the weapon of choice was counter-intuitive – shotgun  less injuries, no weapon at all  more injuries. (The staff tried to prevent the robber if the robber was not armed  robber used violence to secure escape  more injuries to staff.) –Continuous variables used where possible (e.g. loot, distance in km etc.)

There were certain variable blocks used in the model: –background variables and antisociality variables: age, sex, vocation, mentions of drug use etc. These are not known for police at start of investigation, so they will not be included in the final model used to group cases. –”personal style” -variables: target type preferred, in group or alone, weapon of choice, single staff, from main entrance... –”attribute” –variables: loot received, got hurt himself... –”equipment” –variables: amount of disguise, prepared an escape vehicle, chosen weapon, has a bag with him... –”exterior stimulus”: The staff or the customers or a passerby does something, what, is defined in variables. –”reaction to exterior stimulus”: Turns violent, threatens with gun, pushes staff aside and grabs money... –”role”: silent guarding person with weapon, the active person in robbery, the driver... Should the blocks have same amount of variables when factoring?

Study progress Data: all serial commercial robberies from the Greater Helsinki area (Helsinki, Espoo, Vantaa, Kauniainen) from 1992 to 2002 were taken as viable data. As the data seemed large, we dared to measure a multitude of interesting variables from previous research in the data at hand. List of variables as follows:

...and then the usual happened After collecting all the data possible, we are left with 168 robberies, belonging to 76 series with 186 crime-incident behaviours by serial perpetrators. (Doing robberies in small groups is not a rarity.) Too much variables compared to observed cases.

Actions taken Dropped variables that had more than 10% missing values. Still too much variables. Should I drop variables that have no covariance in covariance matrix?

Questions How to separate the ”short-travelers” and the ”long- travelers”?  Idea: separate factor analyses for crime scene behaviour and those variables that have correlation or covariance with distance.  If I receive a factor from latter that correlates strongly with distance (and has sensible eigenvalue, loadings etc.), save the variables as factor-point scores and check the distribution of this scale. Then take the top 1/3 and the bottom 1/3 from this factor i.e. the side that correlate ”+” with distance (long travelers) and the side that correlate ”–” with distance (the short travelers). Other thoughts? What are the initial feelings of Mokken scaling as a method (it is based on Guttman scaling)