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SUMMARY:Metrics and Models: Jakub Bijak
DTSTART;TZID=Europe/London:20260611T140000
DTEND;TZID=Europe/London:20260611T150000
DTSTAMP:20260529T175321Z
UID:cf16314e-b056-f111-a825-6045bd12f634
CREATED:20260523T140426Z
DESCRIPTION:Talk Title: Models as Theory-Building Machines? Insights from 
 Agent-Based Simulations of Human Migration\n\nAbstract: Abstract (150 word
 s): Demography has been famously strong on data and weak on theory. Yet\, 
 early 21st century witnessed renewed interest in enhancing inference about
  observed population patterns (what?) with formal explanations of underlyi
 ng mechanisms (how?) and causal links (why?). One possible class of models
  well suited for building such “theories of the middle range” (RK Mert
 on) for specific demographic processes involves agent-based simulations\, 
 whereby simulated ‘agents’ interact according to a mix of decision rul
 es and empirical data. In this talk\, I will present an example of applyin
 g the agent-based approach to modelling migrant route formation\, integrat
 ing interdisciplinary insights from demography\, statistics\, cognitive ps
 ychology and computer science. Bayesian inference will be used as an integ
 rating perspective\, focusing on the role of uncertainty in shaping model 
 outputs. I will sketch the promises and limitations of this approach\, and
  will invite a discussion of prospects and constraints of using large lang
 uage models for future model-building.\n\nBio: Jakub works as Professor of
  Demographic Science at the Leverhulme Centre of Demographic Science and R
 euben College\, University of Oxford\, having previously spent 17 years at
  the University of Southampton. He holds PhD from Warsaw School of Economi
 cs\, obtained for pioneering research on Bayesian migration forecasting. A
  statistical demographer\, Jakub works on demographic uncertainty\, migrat
 ion and population modelling and forecasting\, and demography of armed con
 flict\, occasionally venturing into other areas\, such as palaeodemography
 . He led an ERC project Bayesian Agent-Based Population Studies (BAPS\, 20
 17-22\, www.baps-project.eu)\, and a Horizon 2020 collaborative project Qu
 antifying migration scenarios for better policy (QuantMig\, 2020-23\, www.
 quantmig.eu).
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