View source for Methodological Foundations for Probabilistic Geo-Temporal Timelines

Methodological Foundations for Probabilistic Geo-Temporal Timelines: Probabilistic geo-temporal timelines reconstruct historical agents' movements using Bayesian inference over fragmented evidence, assigning probabilities to locations and periods rather than binary assertions. Applied to early modern intellectuals (1550–1750), this methodology addresses archival gaps via evidence weighting, likelihood ratios, and digital tools.

=== Epistemological Challenges ===
Surviving evidence favors institutional records (e.g., university matriculations, court rolls), biasing against itinerants like [[Franciscus Mercurius van Helmont]]. Biases include confessional disparities (Protestant vs. Catholic archives), war destruction (Thirty Years' War), and esoteric secrecy. Gaps average 1–5 years for comparable figures ([[Leibniz itinerary|Leibniz]], [[Spinoza movements|Spinoza]]).

=== Evidence Hierarchy ===
Weights (0.0–1.0):

Autograph/dated letter: 1.0 (irrefutable presence).
Contemporary witness: 0.9 (e.g., diary entry).
Legal/inquisitorial record: 0.75 (movement constraints).
Printer gravity: 0.8 (typesetting oversight implies location).
Network gravity: 0.6 (associate proximity).
Textual inference: 0.4 (MSS access).

Justifications per [[Van Helmont Geo-Temporal Timeline Dataset]] examples.

=== Bayesian Workflow ===
P(H|E) = [P(E|H) P(H)] / P(E), where H is location hypothesis, E evidence.

Set priors from cohort baselines (e.g., 0.3 mobility in Protestant zones).
Compute likelihood ratios, incorporating [[Argument from Silence in Bayesian Historiography|argument from silence]] (high P(E|H) absent → low posterior).
Thresholds: >0.75 assert; 0.5–0.75 plausible; <0.5 uncertain.
Handle dependencies via conditional probabilities.

=== Geolocation and Gap Management ===
Use gazetteers ([[World Historical Gazetteer]]) for toponyms to coordinates. Gaps via maximum entropy (uniform priors absent evidence); interpolation rules: last/next known with transit priors.

=== Digital Tools ===
Recogito for toponym tagging; Nodegoat for networks; QGIS/Kepler.js for visualizations (fuzzy polygons for uncertainty). TEI encoding: <location cert="medium" certainty="0.65">Rome</location>.

=== Applications ===
Reconstruct [[Peripatetic Esotericism|peripatetic esoteric]] paths; correlate with [[Esoteric Maneuverability Score|EMS]]. Case: Van Helmont's Leiden 1676 (P=0.99) disrupts static models.

=== Related Concepts ===
[[Network Gravity in Intellectual History]], [[Argument from Silence in Bayesian Historiography]], [[Peripatetic Esotericism]], [[Lost Esoteric Archives]].