Pausanias Analysis

Connectedness feature reference

Shared Mythic Figure Count

The number of distinct mythic figures shared between the focal place and at least one operational neighbour.

Stored model field: shared_mythic_figure_count

-0.178standardized coefficient
Does not survivecurrent direction
255observations summarized
Shared figuresfeature group

How It Is Calculated

Take the union of all focal-place figures found in each local neighbour's figure set, then count the distinct figures.

What a higher value means

More of the focal place's figures also occur in its neighbourhood.

Important qualification. A widely shared figure still counts once, regardless of how many neighbours contain that figure.

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 places25500021158
Survives2040002128
Does not survive5100041158

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)8253960158Does not survive
🌍 Aigina (city)1019198728Survives
🌍 Argos (city)822885327Survives
🌍 Syracuse (Sicily)1129578323Survives
🌍 Olympia (Elis)960546317Survives
🌍 Opous (Locris)825398914Survives

Examples with low recorded values

PlaceMANTO ID ValuePausanias reports
🌍 Abai (Phocis)102746870Survives
🌍 Abia (Messenia)101135050Survives
🌍 Acacesion (Arcadia)101261850Survives
🌍 Ace (Arcadia)102145170Survives
🌍 Acharnai (Attica)101530560Survives
🌍 Acriai (Laconia)101494180Survives

Interpretation in the Predictive Model

Its current standardized coefficient is -0.178, pointing toward does not survive. 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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