Pausanias Analysis

Connectedness feature reference

Shared Action Neighbor-Pattern Count

The total number of qualifying neighbour-by-action combinations.

Stored model field: shared_action_neighbor_pattern_count

-0.112standardized coefficient
Does not survivecurrent direction
255observations summarized
Shared action patternsfeature group

How It Is Calculated

For each local neighbour, count canonical action categories that pass the distinct-figure shared-action rule, then sum those counts across all neighbours.

What a higher value means

The place has more repeated action-pattern connections across its neighbourhood.

Important qualification. Unlike shared action pattern count, the same action contributes again when it is shared with another neighbour.

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 places25500020161
Survives2040002061
Does not survive5100040161

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)8253960161Does not survive
🌍 Argos (city)822885361Survives
🌍 Thessaly905562727Survives
🌍 Aigina (city)1019198724Survives
🌍 Thrace (N. Greece)819561324Survives
🌍 Boiotia819519620Does not survive

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 -0.112, 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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