I was caused to consider the problem of generalisable human behaviour by a presentation on evacuation modelling. In my eyes the ability to model or predict anything, and make the implementation transferable across different contexts is contingent on the assumption that you know how people will act. The fallacy here is that you know how people will act, but you don’t necessarily know how individuals will act. It is easy (relatively) to aggregate across social characteristics and say: young people move at x speed, but old people move at y speed, and use it as a way of building socially stratified and perhaps logically more realistic models (this is often known as disaggregation). This approach seems to work well for regional systems, and large groups of people, however as the system of interest becomes more and more localised, individuals whose observable characteristics diverge enough from a generalisable norm can actually have an important role in the outcome of the model. I tend to think of this group as the 10% who change everything, although the actually percentage is likely to vary contextually.

In my work I have been looking at uptake and registration with GPs (doctors’ surgeries) with a view to isolating the demographic qualifiers of choice that create these different spatial patternings of uptake. Essentially attempting to find interesting social disaggregations within the data. In this work, which is at the level of the surgery, but for a PCT system (i.e. administrative health area), it is clear that some people, a small minority, act unexpectedly and differently to others with the exact same socio-economic characteristics, and that the problem is exacerbated when you look at small and smaller problems. For example, the largest surgeries in Southwark have between 10,000 and 20,000 registered patients, for these it is far easier to model patient registration as a function of distance than it is for a surgery of only 2,000 people. This is because larger surgeries can aggregate out the small number of ‘deviants’ better than a small surgery can. This is a defacto small numbers problem – the effect of a small number of outlying cases has a larger effect on smaller units of aggregation (surgeries) because they make up a larger proportion of the total population.

What does this mean for small-scale agent based simulations then? Well, as far as I can see it is very difficult to predict who out of a population is likely to diverge from their socially-stratified peers and be the outlying individual, and since the scale of simulation is so localised this uncertainty is liable to dramatically change the predicted outcomes. Thus in any case estimating the likely outcome within a margin for error is plausible – x people of y population were subject to some disadvantageous outcome (i.e. death/injury), but assessing where deaths/injuries occured, or the characteristics of who died/was injured may be a bit ambitious, or open to a quantitatively unacceptable uncertainty.

Naturally, understanding local level social systems should be a priority, and deriving generalisable rule-bases to give the best possible outcome for the incidence of a given phenomena is important. However, I think we always have to accept that in these circumstances a small number of people can have a large effect on the outcome in a way which is largely incalculable.

My first CASA working paper is now available. It is the result of a large amount of work I did for my upgrade from MPhil to PhD study at UCL. The topic is “Choice and the Composition of General Practice Patient Registers“. The abstract is as follows:

Choice of general practice (GP) in the National Health Service (NHS), the UKs universal healthcare service, is a core element in the current trajectory of NHS policy. This paper uses an accessibilitybased approach to investigate the pattern of patient choice that exists for GPs in the London Borough of Southwark. Using a spatial model of GP accessibility it is shown that particular population groups make non-accessibility based decisions when choosing a GP. These patterns are assessed by considering differences in the composition of GP patient registers between the current patient register, and a modelled patient register configured for optimal access to GPs. The patient population is classified in two ways for the purpose of this analysis: by geodemographic group, and by ethnicity. The paper considers choice in healthcare for intra-urban areas, focusing on the role of accessibility and equity.

The paper is accessible here.

The above is a quotation from the book “Foucault’s Pendulum” by renowned author Umberto Eco, in the context of the book the phrase relates to a discussion that is had regarding homunculi (singular: homunculus), literally ‘little humans’, which are being kept in a garden in vessels of liquid. When conversation errs towards a human treatment of these creatures, one member of the party remarks “they are only cartesian imps. Or automata”, essentially, it is not appropriate to feel responsibility for these creatures because they are not humans, merely representations of humans.

This led me to consider the position of Geographic Information Science, the ideas of cartesian imps (agent based models?) and automata (cellular automata?) seem to resonate some of the interpretation of Eco’s text, and it highlights some interesting debates. GISci relies on representations and models of reality, it cannot represent the true thing, it was made to generalise, and hence perhaps is a homunculus, the victim of a diminished status in the eyes of those seen to represent the true thing, the real world, in all its relational complexity.

In the Eco text the brief interlude of the homunculus is quickly forgotten with a return to a more established literary tradition: desire. However, it is less easy to turn our back on the same issue in GISci, can we conceivably endorse such a view, that GIS is just a system, a machine for geography? This is the perspective that led to the fiery debates in the 90s between human geographers or social theorists and the GIS community, the tool of GIS was divorced from a human nature, it had no ethic, no morality. This perspective is gradually changing, there is greater engagement with mapping through the naive geographies offered by google maps and co, likewise the GIS establishment have begun to embrace a humanising agenda, from VGI to reconceiving of GIS as media- communication is a powerfully humanising force- to the growth of a critical community that is seeking to rebuild and adapt GIS to a more social means from the inside, not from without. Increasingly GIS is moving away from its positivist roots to include a greater appreciation for human methodologies, one such being the ability of the public to challenge their geographic classification and feedback their experience into the system. Sure, people are still researching voronoi polygons and data structures, but increasingly it seems these projects are being realised in a form that in publically-readable, not merely expert-readable, or (god-forbid) only machine-readable.

I notice that there are stirrings within the GIS community of “the quantitative revolution 2″ (see Mei-Po Kwan and Tim Schwanen), which whilst sounding like a tacky sequel may herald something more than a large budget and meaningless special effects. The tag line of this revolution is: “The critical (re)turn”, I think this is essentially what is required in GIS, and it has been happening anyway, to me the ‘critical (re)turn’ means the inclusion of mixed-methodologies, engaging with people and having a more open and involved discourse. Of course we shall have to wait for Mei-Po and Tim’s paper in a forthcoming Professional Geographer to see whether this is the case, or whether there is something fundamentally more important to say.

From all of this, I guess the question is: to what extent have we humanised the homunculus? or, will we ever get over the fact that it is a homuncuus rather than a human?