Pausanias Analysis

Connectedness feature reference

Maximum Degree of a Large-Place Neighbor

The largest graph-degree value found among the focal place's large operational neighbours.

Stored model field: large_place_max_degree

+0.046standardized coefficient
Survivescurrent direction
255observations summarized
Large-place connectionsfeature group

How It Is Calculated

For local neighbours that meet the large-place threshold, take the maximum place-graph degree; use zero when there is no such neighbour.

What a higher value means

At least one neighbouring large place has more distinct graph ties.

Important qualification. This is controlled by a single neighbour and can move when the MANTO network or large-place threshold changes.

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 places2550002937122
Survives2040002836122
Does not survive510003138122

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
🌍 Aigai (Achaia)10274676122Does not survive
🌍 Aigina (city)10191987122Survives
🌍 Aigina (island)9587597122Survives
🌍 Cleonai (Chalcidice)11307139122Survives
🌍 Cnidos (Asia Minor)11296918122Survives
🌍 Eryx (Sicily)9603207122Survives

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 +0.046, 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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