6 July 2017 Start
7 July 2017 End
United Kingdom University of St. Andrews

e-mail.: [email protected]

Probabilistic Approaches to Uncertainty in Pre-Modern History: A Workshop

Thursday, July 6, 2017 to Friday, July 7, 2017

Myles Lavan (St Andrews) and Daniel Jew (National University of Singapore)

Probability is probably the most powerful conceptual tool that we have yet developed to understand and manage uncertainty. Scientists, demographers and other researchers engaged in forecasting the future regularly use probabilistic techniques to negotiate the massive uncertainties they face in estimating future values of parameters such as global temperature or human population. Yet historians have been slow to see the potential to retroject this approach to the past.

Myles Lavan has recently used ‘Monte Carlo’ probabilistic estimation as the basis of a new approach to the long-standing problem of estimating the spread of Roman citizenship before Caracalla’s universal grant in 212/13 (Past & Present 2016). Daniel Jew is using similar techniques to advance the debate about carrying capacity, labour and land distribution in fourth-century Athens. Both projects use probability as a way of representing our uncertainty about the actual historical values of the key unknown variables.

This workshop is intended to promote and refine the use of probability as a tool for representing uncertainty about historical periods from which little data survives. It will be a hands-on affair devoted to the practicalities of applying a probabilistic analysis to particular historical problems. We will discuss the theory underpinning probabilistic analysis, share our experience in designing and implementing probabilistic models, and discuss some of the conceptual and practical challenges they raise.

The event is open to researchers engaged in parametric modelling (by which we mean the estimation of  unknown quantities on the basis of estimates for other, better-understood parameters, such as Keith Hopkins’ famous model of Roman GDP) who are interested in trialling a probabilistic approach to problems they are working on.  Participation will not require any prior experience with probabilistic approaches, but some facility with numbers and a basic familiarity with MS Excel (or more advanced computational software such as R) are essential.

The workshop is part of a larger AHRC-funded project which aims to demonstrate that probabilistic modes of analysis that have been developed to manage uncertainty in the future can be redeployed as powerful tools of historical analysis. The project has funding to cover some of the cost of accommodation and travel.