babylon.models.entities.consciousness

Ternary consciousness model (Feature 034).

Replaces the stipulated scalar CommunityConsciousness with a 2-simplex model where r + l + f = 1.0. Old fields become computed properties, preserving full backward compatibility (SC-005).

Theoretical basis: George Jackson’s Blood in My Eye — revolutionary consciousness is qualitatively different from the liberal-fascist spectrum. The height above the base (r) measures distance from assimilation.

See also

babylon.models.entities.community: CommunityConsciousness alias. babylon.formulas.consciousness: Computation function. specs/034-ternary-consciousness/spec.md: Feature specification.

Classes

OrgContribution(**data)

An organization's weighted contribution to community consciousness.

ProvenanceLevel(*values)

Data quality indicator for substrate floor computation.

SubstrateFloor(**data)

Per-community-type minimum revolutionary consciousness with provenance.

TernaryConsciousness(**data)

A point in the 2-simplex representing community consciousness.
class babylon.models.entities.consciousness.OrgContribution(**data)[source]

Bases: BaseModel

An organization’s weighted contribution to community consciousness.

Used as input to the compute_ternary_consciousness function.

Parameters:

  • tendency (ConsciousnessTendency) – Which vertex this org pulls toward.

  • membership_density (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Members in community / community population [0, 1].

  • cadre_level (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Organizational development level [0, 1].

  • cohesion (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Internal organizational cohesion [0, 1].

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

tendency: ConsciousnessTendency
membership_density: Probability
cadre_level: Probability
cohesion: Probability
class babylon.models.entities.consciousness.ProvenanceLevel(*values)[source]

Bases: StrEnum

Data quality indicator for substrate floor computation.

Values:

HIGH: Derived from 2+ independent proxy data sources. MEDIUM: Derived from 1 proxy data source. LOW: Estimated from related data, not direct proxy. SYNTHETIC: Stipulated placeholder with no data path.

HIGH = 'high'
MEDIUM = 'medium'
LOW = 'low'
SYNTHETIC = 'synthetic'
class babylon.models.entities.consciousness.SubstrateFloor(**data)[source]

Bases: BaseModel

Per-community-type minimum revolutionary consciousness with provenance.

The substrate floor is consciousness that persists even when all organizations are destroyed — the grandmother teaching not to talk to cops, survival knowledge transmitted through socialization.

Parameters:

  • community_type (CommunityType) – Which community this floor applies to.

  • floor_value (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Minimum r regardless of org landscape [0, 1].

  • confidence (ProvenanceLevel) – Data quality indicator.

  • data_sources (list[str]) – Named data sources used.

  • computation_method (str) – How floor was derived from proxies.

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

community_type: CommunityType
floor_value: Probability
confidence: ProvenanceLevel
data_sources: list[str]
computation_method: str
class babylon.models.entities.consciousness.TernaryConsciousness(**data)[source]

Bases: BaseModel

A point in the 2-simplex representing community consciousness.

Three components (r, l, f) sum to 1.0: - r: Revolutionary consciousness (distance from assimilation). - l: Liberal consciousness (reform within existing order). - f: Fascist consciousness (exclusionary reaction).

Supports two construction paths: 1. Native: TernaryConsciousness(r=0.5, l=0.3, f=0.2) 2. Legacy: ``TernaryConsciousness(collective_identity=0.5,

dominant_tendency=LIBERAL, ideological_contestation=0.4)``

Both produce valid simplex points with backward-compatible properties.

Parameters:

  • r (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Revolutionary component [0, 1].

  • l (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Liberal component [0, 1].

  • f (Annotated[float, Ge(ge=0.0), Le(le=1.0), AfterValidator(func=~babylon.utils.math.quantize)]) – Fascist component [0, 1].

  • contestation_stored (float | None) – Preserved legacy contestation value, or None for natively constructed instances (uses Shannon entropy).

model_config: ClassVar[ConfigDict] = {'frozen': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

r: Probability
l: Probability
f: Probability
contestation_stored: float | None
property collective_identity: float

Oppositional consciousness [0, 1]. Equals r component.

Returns:

The revolutionary component, semantically identical to the old CommunityConsciousness.collective_identity.

property dominant_tendency: ConsciousnessTendency

Prevailing ideological direction (argmax of r, l, f).

Ties are broken in favor of liberal (structural advantage of the status quo — you have to actively organize to leave liberalism).

Returns:

ConsciousnessTendency corresponding to the largest component.

property ideological_contestation: float

Active debate between tendencies [0, 1].

If contestation_stored is set (legacy construction), returns that value for backward compatibility. Otherwise computes normalized Shannon entropy of (r, l, f): H(r,l,f) / log(3).

Returns:

Contestation level. 0 = monopoly, 1 = maximum contestation.

property assimilation_ratio: float

f / (l + f).

Measures how much of the non-revolutionary consciousness is fascist. When l + f is near zero (fully revolutionary), returns 0.5 (neutral).

Returns:

Ratio in [0, 1]. 0 = pure liberal, 1 = pure fascist.

Type:

Position along the liberal-fascist base