353 lines
16 KiB
TeX
353 lines
16 KiB
TeX
%% C2S 2026 Keynote — Simon Carrignon
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%% Computational Cultural Science Workshop, Paris, 18--19 May 2026
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%% École nationale des Chartes -- PSL
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%% Compile with: lualatex slides-c2s-2026.tex
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\begin{beamercolorbox}[wd=\paperwidth, ht=2.5ex, dp=1.5ex, leftskip=4mm, rightskip=4mm]{palette primary}%
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\tiny Simon Carrignon · UCL GEE \hfill
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C2S Workshop, Paris · 18--19 May 2026 \hfill
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\end{beamercolorbox}%
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}
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%% ── Title info ───────────────────────────────────────────────────────────
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\title{Bridging Scales in Cultural Evolution}
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\subtitle{Agent-Based Modelling, Archaeological Patterns,\\and Computational Approaches to Human Cultural Change}
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\author{Simon Carrignon}
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\institute{%
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Department of Genetics, Evolution \& Environment\\
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University College London\\[4pt]
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\small CDAL · ENCOUNTER · UGI
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}
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\date{%
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C2S — Computational Cultural Science Workshop\\
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École nationale des Chartes -- PSL, Paris\\
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18--19 May 2026
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}
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%% ═══════════════════════════════════════════════════════════════════════════
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\begin{document}
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\maketitle
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%% ── Outline ──────────────────────────────────────────────────────────────
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\begin{frame}{Outline}
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\tableofcontents
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\end{frame}
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\section{The Problem: Scales and Data}
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%% ── Frame 1 ──────────────────────────────────────────────────────────────
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\begin{frame}{Computational Methods Have Transformed Cultural Research}
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\begin{columns}[T]
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\begin{column}{0.55\textwidth}
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\textbf{What we can now do:}
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\begin{itemize}
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\item Mine large cultural datasets (texts, images, artefacts)
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\item Extract meaningful patterns without prior theory
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\item Apply ML, Bayesian inference, network analysis,\\dimensionality reduction
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\end{itemize}
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\vspace{6pt}
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\textbf{Result:} unprecedented empirical reach
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\end{column}
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\begin{column}{0.42\textwidth}
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\begin{block}{Key methods}
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\small
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Machine learning\\
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Bayesian inference\\
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Network analysis\\
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Dimensionality reduction\\
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Agent-based modelling
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\end{block}
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\end{column}
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\end{columns}
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\end{frame}
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%% ── Frame 2 ──────────────────────────────────────────────────────────────
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\begin{frame}{But There Are Limits}
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\begin{alertblock}{The bias problem}
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These methods remain biased toward \textbf{certain types of data}
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and \textbf{certain scales of analysis}
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\end{alertblock}
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\vspace{10pt}
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\begin{itemize}
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\item Most work focuses on \emph{large, digitised, recent} corpora
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\item Societies without extensive textual records are underrepresented
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\item Local patterns ≠ global mechanisms
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\end{itemize}
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\vspace{10pt}
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\begin{exampleblock}{The challenge}
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How do we understand \textbf{general human cultural behaviour at scale},\\
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including societies that have left \textbf{few easily interpretable traces}?
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\end{exampleblock}
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\end{frame}
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%% ── Frame 3 ──────────────────────────────────────────────────────────────
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\begin{frame}{The Mesoscale Gap}
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\begin{center}
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\begin{tikzpicture}
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\draw[->, thick, pslblue] (0,0) -- (10,0) node[right] {\textbf{Scale}};
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% Local
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at (1.5,1.2) {\small Local\\interactions};
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% Meso
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\node[draw, rounded corners, fill=pslgold!30, text width=2.5cm, align=center,
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thick, pslgold]
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at (5,1.8) {\textbf{Mesoscale}\\Regional\\Millennial};
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\node[below=2pt] at (5,0.8) {\footnotesize \textit{our target}};
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% Global
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\node[draw, rounded corners, fill=psllight, text width=2.2cm, align=center]
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at (8.5,1.2) {\small Global\\patterns};
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% Arrows
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\draw[->, midgray] (2.5,1.2) -- (3.8,1.5);
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\draw[->, midgray] (7.2,1.2) -- (6.2,1.5);
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\end{tikzpicture}
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\end{center}
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\vspace{4pt}
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\begin{itemize}
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\item Processes unfolding at \textbf{regional level over millennia}
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\item Mechanisms observed locally must be \textbf{extrapolated} carefully
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\item Evidence is often \textbf{archaeological} — fragmented, biased, indirect
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\end{itemize}
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\end{frame}
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\section{The Approach}
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%% ── Frame 4 ──────────────────────────────────────────────────────────────
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\begin{frame}{Our Proposal: Coupling Data and Models}
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\begin{center}
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\begin{tikzpicture}[node distance=3.5cm]
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\node[draw, rounded corners, fill=pslblue!15, text width=3.2cm, align=center,
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minimum height=1.5cm] (data)
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{\textbf{Archaeological\\Data}\\[4pt]\small ML · Bayesian\\pattern extraction};
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\node[draw, rounded corners, fill=pslgold!25, text width=3.2cm, align=center,
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minimum height=1.5cm, right of=data] (model)
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{\textbf{Agent-Based\\Models}\\[4pt]\small Cultural change\\exploration};
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\node[draw, rounded corners, fill=accent!15, text width=3cm, align=center,
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minimum height=1.5cm, right of=model] (hypo)
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{\textbf{Hypothesis\\Testing}\\[4pt]\small Mesoscale\\predictions};
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\draw[->, thick, pslblue, line width=1.5pt] (data) -- (model);
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\draw[->, thick, pslblue, line width=1.5pt] (model) -- (hypo);
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\draw[->, thick, midgray, dashed] (hypo.south) .. controls +(0,-1.2) and +(0,-1.2) ..
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(data.south) node[midway, below] {\small feedback};
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\end{tikzpicture}
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\end{center}
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\end{frame}
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%% ── Frame 5 ──────────────────────────────────────────────────────────────
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\begin{frame}{Why Agent-Based Modelling?}
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\begin{columns}[T]
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\begin{column}{0.5\textwidth}
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\textbf{ABM allows us to:}
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\begin{itemize}
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\item Model \textbf{individual decisions} and local interactions
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\item Observe \textbf{emergent} population-level patterns
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\item Test hypotheses where \textbf{controlled experiments} are impossible
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\item Explore \textbf{counterfactuals} and sensitivity
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\end{itemize}
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\end{column}
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\begin{column}{0.47\textwidth}
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\begin{block}{Epstein (2008)}
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\small ``The agent-based computational model is a new tool for social science\ldots it generates candidate explanations.''
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\end{block}
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\vspace{6pt}
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\begin{block}{Levins (1966)}
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\small Models trade off generality, realism, and precision. Choose deliberately.
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\end{block}
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\end{column}
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\end{columns}
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\end{frame}
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\section{Case Studies}
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%% ── Frame 6 ──────────────────────────────────────────────────────────────
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\begin{frame}{Case Study 1: Cultural Diversity and Taphonomic Bias}
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\begin{itemize}
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\item \textbf{Question:} How does archaeological preservation bias our view\\of past cultural diversity?
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\item \textbf{Approach:} Network-based community detection + ABM
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\item \textbf{Data:} Bronze Age assemblages (BIAD / EPNet datasets)
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\item \textbf{Method:} Simulate cultural exchange networks,\\apply taphonomic loss, compare to empirical patterns
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\end{itemize}
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\vspace{8pt}
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\begin{exampleblock}{Key finding}
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Spatial structure and mobility rates interact to determine\\
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how much diversity is \emph{observable} vs. \emph{lost to the record}
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\end{exampleblock}
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\end{frame}
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%% ── Frame 7 ──────────────────────────────────────────────────────────────
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\begin{frame}{Case Study 2: Patterns at Regional Scale}
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\begin{itemize}
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\item \textbf{Question:} Can we extract meaningful cultural signals\\from heterogeneous archaeological datasets?
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\item \textbf{Approach:} Machine learning + Bayesian classification\\of artefact assemblages
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\item \textbf{Tools:} Dimensionality reduction (PCA, UMAP),\\Bayesian mixture models
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\item \textbf{Coupling:} Patterns inform ABM parameter spaces\\for cultural transmission models
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\end{itemize}
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\vspace{8pt}
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\begin{alertblock}{The challenge of the record}
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Archaeological evidence is fragmentary, spatially biased,\\
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and temporally coarse — methods must account for this explicitly
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\end{alertblock}
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\end{frame}
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%% ── Frame 8 ──────────────────────────────────────────────────────────────
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\begin{frame}{Case Study 3: Modelling Cultural Change Trajectories}
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\begin{itemize}
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\item \textbf{Question:} What cultural transmission processes\\generate the patterns we observe?
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\item \textbf{ABM setup:} Agents represent social groups;\\traits spread via biased transmission, drift, migration
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\item \textbf{Validation:} Simulated distributions compared to archaeological record
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\item \textbf{Scale:} Regional networks over centuries to millennia
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\end{itemize}
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\vspace{8pt}
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\begin{block}{Why this matters for C2S}
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The same pipeline applies to \textbf{textual/cultural corpora}:\\
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extract patterns → model mechanisms → test hypotheses
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\end{block}
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\end{frame}
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\section{Perspectives}
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%% ── Frame 9 ──────────────────────────────────────────────────────────────
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\begin{frame}{Connecting to Computational Cultural Science}
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\begin{columns}[T]
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\begin{column}{0.48\textwidth}
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\textbf{From archaeology to culture broadly:}
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\begin{itemize}
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\item Same questions, different data types
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\item Texts, images, media as ``cultural assemblages''
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\item Disruption metrics (Kim et al. 2026)\\as cultural fitness proxies
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\item NLP + ABM for media dynamics
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\end{itemize}
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\end{column}
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\begin{column}{0.48\textwidth}
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\textbf{Open challenges:}
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\begin{itemize}
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\item Model validation without ground truth
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\item Integrating heterogeneous data types
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\item Interpretability of ML-extracted patterns
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\item Theory–data feedback loops
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\end{itemize}
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\end{column}
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\end{columns}
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\end{frame}
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%% ── Frame 10 ─────────────────────────────────────────────────────────────
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\begin{frame}{Summary}
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\begin{enumerate}
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\item Computational methods have \textbf{transformed} cultural research\\
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but remain biased toward certain data and scales
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\vspace{6pt}
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\item The \textbf{mesoscale} — regional processes over millennia —\\
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is tractable by coupling ML/Bayesian extraction with ABM
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\vspace{6pt}
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\item \textbf{Archaeological evidence} is a hard test case:\\
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methods that work here generalise
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\vspace{6pt}
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\item This pipeline connects directly to broader \textbf{computational\\
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cultural science}: patterns → mechanisms → predictions
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\end{enumerate}
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\end{frame}
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%% ── Thank you ─────────────────────────────────────────────────────────────
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\begin{frame}[standout]
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\centering
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\Large Thank you\\[12pt]
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\normalsize
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\href{mailto:s.carrignon@ucl.ac.uk}{s.carrignon@ucl.ac.uk}\\[6pt]
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UCL GEE · CDAL · ENCOUNTER · UGI\\[10pt]
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\small
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Slides \& code: \href{https://github.com/simoncarrignon}{github.com/simoncarrignon}\\[16pt]
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\textit{Computational Cultural Science Workshop}\\
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École nationale des Chartes -- PSL · Paris · May 2026
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\end{frame}
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%% ── Backup slides ─────────────────────────────────────────────────────────
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\appendix
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\begin{frame}{References}
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\small
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\begin{itemize}
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\item Epstein, J.M. (2008). Why Model? \textit{JASSS} 11(4):12.
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\item Levins, R. (1966). The strategy of model building in population biology.
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\textit{Am. Sci.} 54:421--431.
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\item Bonabeau, E. (2002). Agent-based modeling. \textit{PNAS} 99:7280--7287.
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\item Reichenbach et al. (2007). Mobility promotes and jeopardizes biodiversity.
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\textit{Nature} 448:1046--1049.
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\item Kim, Kojaku \& Ahn (2026). Uncovering simultaneous breakthroughs.
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\textit{Science Advances} 12(14).
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\end{itemize}
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\end{frame}
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\begin{frame}{The Archaeological Record: Key Challenges}
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\begin{itemize}
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\item \textbf{Preservation bias:} organic materials lost; hard materials persist
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\item \textbf{Spatial bias:} sampling effort uneven across regions
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\item \textbf{Temporal resolution:} centuries collapsed into single ``phases''
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\item \textbf{Inference gap:} behaviour → material culture → preservation → observation
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\end{itemize}
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\vspace{6pt}
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Methods must be \textbf{explicitly designed} to account for these filters,\\
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not applied naively from other domains.
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\end{frame}
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\end{document}
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