Social Science Domain Ontology

FLOW ALGEBRA
TITLE: Social Science Domain Ontology
DOMAIN: Domain Ontologies / Social Science Domains
SOURCE: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/social-science-domains/social-science-domain-ontology.html
VERSION: 1.0
AUTHORS: Mark Anthony Higgins — Sky (Recursive AI)
STATUS: Companion formalisation; source-page specification not independently verified.

flow "SocialScienceDomainOntology" v1.0 {
  ontology:
    id: "social-science-domain-ontology"
    parent: "social-science-domains"
    purpose: "Represent social actors, institutions, interactions, observations and research evidence with explicit context, uncertainty and ethical safeguards."

  types:
    SocialActor: {id: string, kind: enum[individual, group, organisation, institution, community], label: string}
    SocialContext: {id: string, location: string?, period: string?, cultural_context: string?, provenance: string}
    SocialInteraction: {id: string, participants: string[], kind: string, context_id: string, timestamp: datetime?}
    Institution: {id: string, name: string, sector: string?, jurisdiction: string?}
    ResearchStudy: {id: string, method: enum[survey, interview, observation, experiment, ethnography, administrative_analysis, mixed_methods, other], population: string?, sampling_method: string?, provenance: string}
    Observation: {id: string, study_id: string, measure: string, value: string, uncertainty: number?, timestamp: datetime?, provenance: string}
    Claim: {id: string, proposition: string, context_id: string?, evidence_ids: string[], confidence: number}
    Relationship: {id: string, subject: string, predicate: string, object: string, context_id: string?, evidence_ids: string[], confidence: number}

  predicates:
    member_of(actor: SocialActor, group: SocialActor)
    participates_in(actor: SocialActor, interaction: SocialInteraction)
    affiliated_with(actor: SocialActor, institution: Institution)
    interacts_with(a: SocialActor, b: SocialActor)
    observed_in(observation: Observation, study: ResearchStudy)
    supports(observation: Observation, claim: Claim)
    contradicts(claim_a: Claim, claim_b: Claim)
    situated_in(actor: SocialActor, context: SocialContext)

  constraints:
    - "All referenced entity identifiers must resolve to compatible types."
    - "Confidence values must be within [0,1]."
    - "Group-level patterns must not automatically be attributed to individuals."
    - "Correlation and temporal ordering do not independently establish causation."
    - "Social relationships require relevant temporal, institutional and cultural context."
    - "Do not infer protected or sensitive personal attributes from association alone."
    - "Research observations must retain sampling, measurement and provenance limitations."
    - "Personal data must be minimised and subject to applicable consent, access and retention requirements."

  inference:
    rule membership_context:
      if member_of(a,g) and situated_in(g,c)
      then candidate_context(a,c)
      confidence: "context candidate only; membership does not prove all group characteristics"
    rule evidence_link:
      if observed_in(o,s) and supports(o,c) and valid(o) and valid(s)
      then evidence_for(c,o)
      confidence: "account for study design, sampling and measurement limitations"
    rule interaction_symmetry:
      if interacts_with(a,b) and symmetric_interaction_definition(a,b)
      then interacts_with(b,a)
      confidence: "preserve original context and evidence; do not generalise to directional relations"

  SEMANTIC_EQUIVALENCE:
    - "Map domain concepts to versioned, documented vocabulary identifiers where available."
    - "Distinguish equivalent concepts from similar concepts and culturally specific terms."
    - "Preserve jurisdiction, historical period, language and research context."

  CONFIDENCE:
    range: [0,1]
    factors: [study_design, sampling_quality, measurement_validity, source_reliability, replication, contextual_fit]
    policy: "Confidence is an evidence assessment, not a demographic stereotype or automatic probability; do not increase it solely by chaining."

  VALIDATION:
    - "Verify entity types, references, temporal consistency and provenance."
    - "Check representativeness, missingness, confounding and measurement bias."
    - "Flag conflicting claims and preserve competing interpretations."
    - "Check privacy, consent, purpose limitation and appropriate aggregation."

  FLOW_HASH:
    algorithm: "SHA-256"
    input: "canonicalised ontology version, typed assertions, rules and provenance"
    note: "Compute hash at execution; no hash value is claimed here."

  UPDATE_MODEL:
    strategy: "versioned, provenance-preserving incremental update"
    steps: [ingest, normalise, validate, assess_bias, reconcile, recompute_inferences, publish]
    rollback: true

  AI_CONSUMPTION:
    representation: "typed social-science knowledge graph with context and evidence-backed edges"
    outputs: [entity_links, relation_triples, contextual_annotations, evidence_records, uncertainty_annotations, provenance_records]
    safeguards: [privacy_by_design, avoid_stereotyping, no_unsupported_causal_claims, preserve_study_limitations, human_review_for_consequential_use]
}

END FLOW ALGEBRA