Psychology Domain Ontology

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

flow "PsychologyDomainOntology" v1.0 {
  ontology:
    id: "psychology-domain-ontology"
    parent: "social-science-domains"
    purpose: "Represent psychological constructs, behavioural observations, research designs and evidence-supported relationships without conflating association with causation."

  types:
    Person: {id: string, pseudonymised: boolean, consent_basis: string?}
    Population: {id: string, inclusion_criteria: string, context: string?}
    PsychologicalConstruct: {id: string, name: string, operational_definition: string, theoretical_framework: string?}
    Behaviour: {id: string, description: string, context: string?, observed_at: datetime?}
    CognitiveProcess: {id: string, name: string, description: string}
    Emotion: {id: string, label: string, measurement_method: string?}
    MeasurementInstrument: {id: string, construct_id: string, scale: string, reliability: number?, validity_evidence: string[]}
    Observation: {id: string, subject_id: string?, construct_id: string?, value: number?, unit: string?, timestamp: datetime?, method: string, provenance: string}
    Study: {id: string, design: enum[experimental, observational, longitudinal, cross_sectional, qualitative, mixed_methods], population_id: string, ethics_approval: string?, provenance: string}
    Intervention: {id: string, description: string, protocol: string?, study_id: string?}
    Finding: {id: string, study_id: string, claim: string, effect_size: number?, uncertainty: string?, evidence: string[]}
    Relationship: {id: string, subject: string, predicate: string, object: string, context: string?, confidence: number, evidence: string[]}

  predicates:
    measures(instrument: MeasurementInstrument, construct: PsychologicalConstruct)
    observes(observation: Observation, construct: PsychologicalConstruct)
    participates_in(person: Person, study: Study)
    investigates(study: Study, construct: PsychologicalConstruct)
    associated_with(a: PsychologicalConstruct, b: PsychologicalConstruct)
    predicts(a: PsychologicalConstruct, b: PsychologicalConstruct)
    influences(intervention: Intervention, construct: PsychologicalConstruct)
    supports(finding: Finding, claim: string)
    contradicts(finding: Finding, claim: string)
    derived_from(finding: Finding, study: Study)

  constraints:
    - "All relationship endpoints must resolve to compatible typed entities."
    - "Confidence must lie within [0,1]."
    - "Psychological constructs require operational definitions before quantitative comparison."
    - "Measurements must retain scale, method, population, context and uncertainty where available."
    - "Correlation or prediction alone must not be promoted to causal influence."
    - "Instruments require population-appropriate reliability and validity evidence."
    - "Protect personal data, consent boundaries and sensitive psychological records."
    - "Do not infer a clinical diagnosis from isolated traits, scores or behaviours."

  inference:
    rule measurement_support:
      if measures(i,c) and observes(o,c) and valid_instrument(i,o)
      then evidence_for(o,c)
      confidence: "bounded by measurement quality and contextual validity"
    rule evidence_link:
      if derived_from(f,s) and supports(f,claim) and valid(s)
      then evidence_backed(claim,s)
      confidence: "retain study limitations and provenance"
    rule association_guard:
      if associated_with(a,b)
      then causal_status(a,b,"unestablished")
      confidence: "association does not establish causation"

  SEMANTIC_EQUIVALENCE:
    - "Align constructs only when definitions, instruments, populations and contexts are compatible."
    - "Distinguish related constructs from interchangeable constructs."
    - "Preserve source terminology and versioned mapping provenance."

  CONFIDENCE:
    range: [0,1]
    factors: [study_quality, sample_representativeness, measurement_reliability, construct_validity, replication, confounding, uncertainty]
    policy: "Do not increase confidence merely by chaining dependent findings or repeating the same evidence."

  VALIDATION:
    - "Validate type compatibility, operational definitions, study design and evidence provenance."
    - "Check reliability, measurement invariance and population applicability where relevant."
    - "Flag unsupported causal claims, inconsistent findings and missing ethical safeguards."
    - "Distinguish statistical significance from practical importance."

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

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

  AI_CONSUMPTION:
    representation: "typed, evidence-backed psychological knowledge graph"
    outputs: [construct_links, study_links, relationship_triples, uncertainty_annotations, provenance_records]
    safeguards: [privacy_preservation, no_unsupported_diagnosis, no_causal_overclaim, preserve_context_and_population]
}

END FLOW ALGEBRA