School Shootings – Can Potential Shooter Profiles be Identified?

January 8, 2013

In light of the recent shootings, in Newtown, Connecticut. New debates have been sparked on the idea of gun control and identification of potentially unstable individuals who could commit such crimes.

An article on Science Daily website, School Shootings: What We Know and What We Can Do, highlighted some recent research studying past events and tragedies to accumulate a profile of potential shooters and how these individuals can be identified ahead of time. The article uses research by Dr. Daniel J. Flannery on explaining how shooters demonstrate similar features such as depression, low self-esteem, narcissism and a fascination with death. However these key aspects and similarities across shootings are not strong enough to produce conclusive profiles which could allow for future prevention of such tragedies.

Other research has produced similar findings, Leary, Kowalski, Smith and Philips (2003) analysed multiple shootings between 1995 to 2001. They found that depression, low self-esteem and narcissism were all present in the individuals involved in the shootings. However they all also shared one more common attribute and that was social rejection. Social rejection alone cannot fully explain these acts of violence as most people navigate through life and at some stage are exposed to social rejection. However this social rejection coupled with psychological problems or a fascination with death may lead to acts of violence occurring.

Unfortunately research in this area is inconclusive and therefore specific attributes and characteristics have not been idenitifed to put in place preventative measures to reduce the chances of such tragedies occuring again.

– Stefano


Human Sciences, Statistics, and R

January 6, 2013

The use of statistics has long been important in the human sciences. An early example is an analysis by William Sealy Gosset (alias “Student”) of biometric data obtained by Scotland Yard around 1900. The heights of 3,000 male criminals fit a bell curve almost perfectly:


Histogram © A. H. Dekker, produced using R software

Standard statistical methods allow the identification of correlations, which mark possible causal links:


XKCD teaches us that “Correlation doesn’t imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing ‘look over there.’”

Newer, more sophisticated statistical methods allow the exploration of time series and spatial data. For example, this project looks at the spatial distribution of West Nile virus (WNV) – which disease clusters are significant, and which are merely tragic coincidence:


Distribution of significant clusters of human WNV in the Chicago region, from Ruiz et al.

SPSS has been the mainstay of statistical analysis in the human sciences, but many newer techniques are better supported in the free R toolkit. For example, this paper discusses detecting significant clusters of diseases using R. The New York Times has commented on R’s growing popularity, and James Holland Jones points out that R is used by the majority of academic statisticians (and hence includes the newest developments in statistics), R has good help resources, and R makes really cool graphics.


A really cool graph in R, using the ggplot2 R package (from Jeromy Anglim’s Psychology and Statistics Blog)

An increasing quantity of human-science-related instructional material is available in R, including:

Through the igraph, sna, and other packages (and the statnet suite), R also provides easy-to-use facilities for social network analysis, a topic dear to my heart. For example, the following code defines the valued centrality measure proposed in this paper:

library("igraph")
valued.centrality <- function (g) {
  recip <- function (x) if (x == 0) 0 else 1/x
  f <- function (r) sum(sapply(r, recip)) / (length(r) - 1)
  apply (shortest.paths(g), MARGIN=1, f)
}

This definition has the advantage of allowing disconnected network components, so that we can use these centrality scores to add colour to a standard plot (using the igraph package within R):


Social network diagram, produced using R software, coloured using centrality scores

– Tony


The future world of neuroscience

October 3, 2012

English: Drawing of the human brain, from the ...

Just read a post on the increasing ability of neuroscientists to image and understand the brain.  The author, Kathleen Taylor makes a very interesting observation that perhaps in the future the research of the brain will surpass the physical sciences in importance.  She is probably biased given her neuroscience background but I feel that she has highlighted some fundamental questions with regard to how humans will interact with the world (or perhaps the universe?) and with each other in the future.

She makes the point that the physical sciences have largely been insulated from how the knowledge gained from research in this area is used, given that there is no human input into their experimentation.  The research is largely introspective or governed by mathematics or similarly prescriptive methods.  The potential consequences of the research is not addressed at any time (at least in a formal sense) as there is little input from others apart from peers and supervisors with a similar research background.

The difference between the physical and social sciences has been commented on in previous blog posts.  Physical scientists, although brilliant in their own field, tend to make assumptions as to how humans fit into their models and how their research can be applied.  Human behaviour is commonly included as a probability which then influences the remainder of the postulated model to provide results which do not necessarily reflect what actually happens in the real world.  However, either these discrepancies are ignored, or assumed to be just part of a distribution of human behaviour.  A system is then designed using such flawed thinking and typically, it is the poor old human operators who have to adapt and make up for such sloppy design when they have to make things work.

Alternatively, these operators are seen as the problem when the system is subsequently audited as the ‘brilliant’ system design is hardly ever tested and/or seen to be at fault.  At last there are glimmers of hope as safety management systems are identifying that these ‘brilliant’ systems are more often than not the cause of many failings, not just from the operator perspective.  So the ‘human error‘ which historically has almost always been attributed as the cause of an accident is sheeted home to where it belonArachnoidgs in the first place – the arrogant human who designed the system who was either unaware of or was permitted to ignore the fact that an inherent part of the design process is to understand how the human operator thinks and acts when interfacing with their system.

On the other hand, social scientists and human scientists in particular have a core theme that human behaviour is far more complex and determined by sensory and perceptual aspects initially, then modified by cognitive processes which are also subject to change.  These factors need to be addressed when modelling how a human operates with a machine or amongst themselves to make decisions etc.  As discussed in Kathleen’s article, the brain is such a complex organ and it is subject to a massive range of inputs that we are only now becoming aware of how it works, and how to manipulate it.  Perhaps in the new millennium, neuroscience may have similar advances as occurred in physics (relativity, quantum mechanics and understanding of atomic and sub-atomic structure for example) during the last.

Kathleen highlights that the ethics of operating on the neural and molecular scale within the human brain and the resultant impact it may have on the individual concerned will be a central theme going forward.  This is especially pertinent when entities such as commercial or government interests will be in a position to manipulate these factors and it is therefore something which needs to be addressed well prior to this particular genie escaping the bottle.

Which leads back to KathleEnglish: Computer tomography of human brain, f...en’s major point.  She contends that neuroscience may overtake the physical sciences as the whole consciousness experience will determine how the human species develops into the future.  The social/psychological/physiological sciences understand these aspects and, most importantly, understand the need for an ethical framework when addressing these matters.  So at least we will be better placed than the current situation, where the physical scientists, who have neither of these fundamentals, seem to determine how technology develops and is applied.  Perhaps we will then have a more level research field where social and human scientists are included at the very beginning and can (heaven forbid!) inform how technology is developed and applied to best advantage for the human user who will ultimately directly interact with it.