Carceral Geography

Carceral Geography models the spatial dimensions of state repression: where populations are detained, displaced, and eliminated. It implements the detention pipeline and displacement routing systems.

Overview

The carceral geography system tracks how the state uses space as a tool of class management:

Detention - Removing populations from economic circulation
Displacement - Forcing populations to move between territories
Elimination - Permanent removal from the simulation

This models real-world patterns: mass incarceration, gentrification, border enforcement, and colonial dispossession.

The Detention Pipeline

When state repression targets a class, it enters a three-stage pipeline:

        stateDiagram-v2
    [*] --> DETENTION: Arrest
    DETENTION --> INCARCERATION: After detention_duration
    INCARCERATION --> ELIMINATION: displacement_priority
    DETENTION --> [*]: Release
    INCARCERATION --> [*]: Labor scarce mode

    note right of DETENTION: Short-term hold<br/>Can be released
    note right of INCARCERATION: Long-term hold<br/>Reduced capacity
    note right of ELIMINATION: Removed from<br/>simulation

Stage Transitions:

Detention → Incarceration After detention_duration ticks, detained classes move to incarceration.
Incarceration → Elimination/Release Based on displacement_priority mode: - ELIMINATION mode: Classes are eliminated - LABOR_SCARCE mode: Classes are released (needed for production) - BALANCED mode: Probabilistic outcome

Displacement Priority Modes

The displacement_priority parameter controls how the state manages surplus populations:

Displacement Priority Modes
Mode	Logic	Historical Parallel
LABOR_SCARCE	Prefer release; labor is valuable	Post-war labor shortages
BALANCED	Mixed approach based on conditions	Normal capitalist state
ELIMINATION	Prefer elimination; populations disposable	Settler colonialism, fascism

Dynamic Mode Selection:

The mode can be set statically or computed dynamically based on economic conditions:

def calculate_displacement_priority(territory, graph):
    """Dynamic priority based on labor market."""
    labor_supply = count_available_workers(territory, graph)
    labor_demand = calculate_production_needs(territory, graph)

    if labor_supply < labor_demand * 0.5:
        return DisplacementPriority.LABOR_SCARCE
    elif labor_supply > labor_demand * 1.5:
        return DisplacementPriority.ELIMINATION
    else:
        return DisplacementPriority.BALANCED

Territory Heat System

Territories accumulate heat from high-profile activities:

\[H_{t+1} = H_t + \Delta H_{activity} - \Delta H_{decay}\]

Heat Sources:

Protests, strikes (high heat gain)
Organizing activities (medium heat gain)
Normal economic activity (no heat change)

Heat Consequences:

Heat Thresholds
Heat Level	Consequence
< 0.4	Normal operations
0.4 - 0.8	Increased surveillance
>= 0.8	Eviction trigger - classes must relocate

Eviction and Spillover

When territory heat reaches 0.8, the eviction pipeline activates:

Mark for Eviction Classes with TENANCY edges to hot territory are flagged.
Find Adjacent Territory System searches ADJACENCY edges for relocation targets.
Execute Displacement Classes move to adjacent territory; heat spillover occurs.

def process_eviction(class_id, hot_territory, graph):
    """Execute eviction from hot territory."""
    # Find adjacent territories
    adjacent = [
        t for t in graph.neighbors(hot_territory)
        if graph.edges[hot_territory, t].get("edge_type") == EdgeType.ADJACENCY
    ]

    if adjacent:
        # Move to lowest-heat adjacent territory
        target = min(adjacent, key=lambda t: graph.nodes[t]["heat"])
        relocate_class(class_id, hot_territory, target, graph)

        # Heat spillover
        graph.nodes[target]["heat"] += SPILLOVER_COEFFICIENT
    else:
        # No escape route - enter detention
        enter_detention(class_id, hot_territory, graph)

Operational Profiles

Territories have operational profiles that affect heat dynamics:

Operational Profiles
Profile	Heat Gain Rate	Description
HIGH_PROFILE	High	Visible areas (city centers, protest sites)
MIXED	Medium	Normal urban/suburban areas
LOW_PROFILE	Low	Hidden areas (rural, underground)

Strategic Implications:

Organize in LOW_PROFILE territories to avoid heat
HIGH_PROFILE territories draw state attention but enable mass mobilization
Movement between profiles affects surveillance exposure

Integration with Other Systems

Carceral geography interacts with:

Survival System: Detention reduces P(S|A) - survival by acquiescence becomes impossible while detained. This can trigger revolutionary consciousness.
Solidarity System: Detained classes lose SOLIDARITY edges (network fragmentation). Prison organizing can rebuild them.
Contradiction System: Mass incarceration increases systemic tension. When detention capacity is exceeded, contradictions intensify.

Implementation

The carceral geography system is implemented in TerritorySystem:

# src/babylon/engine/systems/territory.py

class TerritorySystem:
    def process(self, graph, services, context):
        # 1. Update heat based on activities
        self._update_heat(graph)

        # 2. Process evictions from hot territories
        self._process_evictions(graph)

        # 3. Advance detention pipeline
        self._advance_detention(graph, context.config)

        # 4. Route displaced populations
        self._route_displacement(graph, context.config)

Key Configuration

GameDefines parameters for carceral geography:

Configuration Parameters
Parameter	Default	Effect
`territory.heat_threshold`	0.8	Heat level triggering eviction
`territory.heat_decay`	0.1	Heat reduction per tick
`territory.spillover_coefficient`	0.2	Heat transferred on spillover
`territory.detention_duration`	5	Ticks before detention → incarceration
`territory.displacement_priority`	BALANCED	Default displacement mode