Descrizione del progetto
Gli eventi del passato ritornano nel presente?
La teoria secondo cui la storia tende a ripetersi è molto diffusa. Come agisce questa tendenza nelle guerre? Il progetto PaCE, finanziato dall’UE, studierà i modelli ricorrenti nello scoppio e nell’inasprimento delle guerre combinando nuovi metodi (che prevedono lo studio delle caratteristiche della sequenza degli eventi, piuttosto che dei loro valori grezzi) e i dati sui conflitti per estrarre motivi prebellici tipici. Il progetto individuerà modelli applicabili al periodo compreso tra l’inizio della prima guerra mondiale e i lanci di razzi da parte di Hamas e studierà le percezioni avvalendosi di dati provenienti da mercati finanziari, articoli e documenti diplomatici. PaCE valuterà inoltre i possibili limiti fondamentali alla prevedibilità dei conflitti.
Obiettivo
Are there recurring patterns in the escalation and emergence of wars? The idea that history may repeat itself is old. But
recent advances overcoming methodological and data barriers present an opportunity to identify these recurrences
empirically and to examine whether these patterns can be classified to improve forecasts and inform theories of conflict. I
propose to combine new methods—using the shape of the sequence of events rather than its raw values—and novel data
on conflict from finance, diplomatic cables, and newspapers, to extract typical pre-war motifs. Just as DNA sequencing has
been critical to medical diagnoses, PaCE aims to diagnose international politics by uncovering the relevant patterns in the
area of conflict. Our goals are to:
(i) Identify patterns in the pre-conflict actions using data on conflict events—from the onset of WWI to Hamas’s rocket
launches—and in their perceptions using data from financial markets (the “crowd’s” perception), news articles (the “experts”),
and diplomatic documents (the policy-makers). This will allow us to evaluate the patterns of escalation over different
timescales—from the decade to the minute. The similarity between temporal sequences will be measured using algorithms
which allow for flexible matching, such as Dynamic Time Warping.
(ii) Evaluate the utility of these patterns to improve forecasts of conflict with both historical and live out-of-sample
predictions. Our results, using shape-based classification methods, will be made public and evaluated in real time. Moreover,
using new measures of complexity to distinguish regular, chaotic, and random behavior, I will measure possible fundamental
limits to the predictability of conflict events.
(iii) Summarize the core features of dangerous patterns into motifs—recurring patterns—that can help build new
theories of conflict emergence and escalation. PaCE will build a repository of shapes—a grammar of patterns—to be used
as the building blocks of new theories.
Campo scientifico
Parole chiave
Programma(i)
Argomento(i)
Meccanismo di finanziamento
ERC-COG - Consolidator GrantIstituzione ospitante
D02 CX56 DUBLIN 2
Irlanda