Pausanias Analysis

Connectedness feature reference

Large-Place Neighbor Count

The number of operational neighbours classified as large network places.

Stored model field: large_place_neighbor_count

+0.178standardized coefficient
Survivescurrent direction
255observations summarized
Large-place connectionsfeature group

How It Is Calculated

Identify places in the top configured quantile for either graph degree or PageRank, then count how many of the focal place's local neighbours belong to that set.

What a higher value means

The place has ties to more highly connected places in the MANTO graph.

Important qualification. β€œLarge” means network-prominent under the configured threshold, not physically large or historically populous.

Current Model Cohort

These descriptive statistics use the current labelled cohort after aliases have been collapsed to one row per MANTO place.

GroupN MinimumQ1 MedianMean Q3Maximum
All labelled places2550002233
Survives2040002220
Does not survive510003233

Examples from the Current Data

Examples are descriptive checks on the calculated feature. Their outcome labels report what Pausanias says; they do not establish that the feature caused survival or abandonment.

Examples with high recorded values

PlaceMANTO ID ValuePausanias reports
🌍 Thebes (Boiotia)825396033Does not survive
🌍 Coroneia (Thessaly)1130738020Survives
🌍 Aigina (island)958759719Survives
🌍 Libya (North Africa)825395119Does not survive
🌍 Trachis (Thessaly)825403318Does not survive
🌍 Haliartos (Boiotia)965195615Survives

Examples with low recorded values

PlaceMANTO ID ValuePausanias reports
🌍 Abia (Messenia)101135050Survives
🌍 Ace (Arcadia)102145170Survives
🌍 Acharnai (Attica)101530560Survives
🌍 Acriai (Laconia)101494180Survives
🌍 Aegina (Epidauria)113081850Survives
🌍 Agrai (Attica)101515480Survives

Interpretation in the Predictive Model

Its current standardized coefficient is +0.178, pointing toward survives. This means that a one-standard-deviation increase changes the fitted log odds in that direction while the other included features are held fixed.

Because the connectedness features are correlated and the model's out-of-fold performance is weak, this is a conditional associationβ€”not a standalone ranking, causal effect, or historical explanation.

Related Features

Data Scope

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