Layer 3: Rules

How Artifacts BEHAVE¶

Layer 3 defines operational rules—automated behaviors, policy enforcement, and governance controls that determine what happens when artifacts reach certain states. This is where knowledge management becomes automated, compliant, and scalable.

The Governance Challenge¶

As documentation systems scale, manual oversight becomes impossible:

1,000 documents: One person can maintain awareness
10,000 documents: Need dashboards and queries
100,000+ documents: Must automate governance

Layer 3 provides the rule engine for scaled knowledge management.

Three Anthropological Axes¶

Layer 3 is grounded in a systematic philosophical framework with three axes of human activity:

Circular Axis (Human ↔ Human)¶

Domain: Collaboration, consent, authority, roles

Governance concerns:

Who can approve publication?
What consent is needed for sharing?
Which roles have edit authority?
How do we handle disputes?

Example rules:

rule: publication_approval
  conditions:
    - refinement >= 0.90
    - stubs.count == 0
    - audience == 'published'
  actions:
    - require_approval:
        roles: ['senior_researcher', 'pi']
        minimum: 2
    - notify: 'editorial_team'
    - audit: 'publication_request'

Radial Axis (Human ↔ World)¶

Domain: Tools, infrastructure, dependencies, risk

Governance concerns:

What’s the blast radius if this document has errors?
Which systems depend on this specification?
What infrastructure changes trigger updates?
How do we manage cascading failures?

Example rules:

rule: dependency_check
  conditions:
    - network_position == 'hub'
    - health in ['poor', 'critical']
  actions:
    - block_edit: false  # allow fixes
    - notify_dependents: true
    - escalate_priority: 'critical'
    - audit: 'hub_degradation'

Angular Axis (Human ↔ Ideational)¶

Domain: Standards, policies, norms, compliance

Governance concerns:

Does this meet regulatory requirements?
Are style guides being followed?
Is the methodology sound?
Does content align with organizational values?

Example rules:

rule: compliance_validation
  conditions:
    - audience in ['public', 'published']
    - compliance_fit != 'compliant'
  actions:
    - block_publication: true
    - notify: 'compliance_team'
    - require_review:
        roles: ['legal', 'compliance_officer']
    - audit: 'compliance_block'

Core Capabilities¶

1. Automation¶

Purpose: Reduce manual work, ensure consistency

Example: Auto-Promote Artifacts¶

rule: auto_promote_to_review
  trigger: 'on_save'
  conditions:
    - refinement >= 0.70
    - stubs.count <= 1
    - stage == 'develop'
    - form in ['stable', 'evergreen']
  actions:
    - set_stage: 'review'
    - notify_reviewers:
        roles: ['peer_reviewer']
        message: "Document ready for review"
    - update_metadata:
        review_requested_at: now()
    - audit: 'auto_promotion'

Effect: Documents that reach quality thresholds automatically enter review without manual tracking.

Example: Archive Stale Documents¶

rule: auto_archive_stale
  trigger: 'daily_scan'
  conditions:
    - drift in ['significant', 'severe']
    - days_since_access > 365
    - form == 'transient'
    - retention_value in ['low', 'disposable']
  actions:
    - set_form: 'archived'
    - move_to: 'archive/auto_archived/'
    - notify_author:
        message: "Document auto-archived due to inactivity"
    - audit: 'auto_archive'

2. Enforcement¶

Purpose: Block actions that violate policies

Example: Prevent Publication of Incomplete Work¶

policy: publication_gate
  scope: ['audience: published']
  enforcement: 'blocking'
  requirements:
    - refinement >= 0.90
    - stubs.count == 0
    - compliance_fit == 'compliant'
    - peer_reviews >= 2
  violation_action:
    - block_save: true
    - show_error: |
        Cannot publish: Requirements not met
        - Refinement: {refinement} (need 0.90+)
        - Stubs: {stubs.count} (need 0)
        - Reviews: {peer_reviews} (need 2)
    - audit: 'publication_gate_violation'

Effect: Authors cannot set audience: published unless all criteria are met.

Example: Protect Critical Infrastructure Docs¶

policy: hub_protection
  scope: ['network_position: hub']
  enforcement: 'blocking'
  requirements:
    - health in ['excellent', 'good']
    - review_frequency: 'monthly'
    - approvals_required: 2
  rules:
    - prevent_deletion: true
    - require_approval_for_major_changes: true
    - notify_on_any_change: ['documentation_team']
  violation_action:
    - block_action: true
    - escalate_to: ['tech_lead', 'documentation_manager']
    - audit: 'hub_protection_violation'

3. Governance¶

Purpose: Implement role-based controls and consent management

Example: Multi-Level Approval Workflow¶

workflow: external_publication
  stages:
    - name: 'draft'
      allowed_roles: ['author', 'contributor']
      exit_gate:
        refinement >= 0.70
        
    - name: 'peer_review'
      allowed_roles: ['peer_reviewer']
      required_approvals: 2
      approval_roles: ['senior_researcher']
      exit_gate:
        refinement >= 0.85
        all_reviews_complete: true
        
    - name: 'legal_review'
      allowed_roles: ['legal', 'compliance_officer']
      required_approvals: 1
      approval_roles: ['legal']
      exit_gate:
        compliance_fit == 'compliant'
        legal_clearance: true
        
    - name: 'final_approval'
      required_approvals: 1
      approval_roles: ['pi', 'director']
      exit_gate:
        refinement >= 0.90
        stubs.count == 0
        
    - name: 'published'
      immutable: true
      audit_all_access: true

policy: data_sharing_consent
  scope: ['content_type: dataset', 'audience: public']
  enforcement: 'blocking'
  requirements:
    - consent_forms: ['participant_consent', 'irb_approval']
    - anonymization_verified: true
    - data_privacy_review: 'approved'
  actions:
    - verify_consent:
        check_expiration: true
        check_revocations: true
    - audit:
        include: ['consent_ids', 'verification_timestamp']
  violation_action:
    - block_publication: true
    - notify: ['legal', 'irb_coordinator', 'pi']
    - require_review: true

4. Notification¶

Purpose: Alert stakeholders of critical states

Example: Drift Alert for Evergreen Docs¶

rule: evergreen_drift_alert
  trigger: 'daily_scan'
  conditions:
    - form == 'evergreen'
    - drift in ['moderate', 'significant', 'severe']
    - network_position in ['hub', 'connector']
  actions:
    - calculate_staleness_score: true
    - notify_author:
        frequency: 'weekly'
        message: |
          Document drift detected:
          - Days since edit: {days_since_edit}
          - Current drift: {drift}
          - Network impact: {affected_docs} documents
    - escalate_if:
        condition: drift == 'severe' AND network_position == 'hub'
        notify: ['documentation_manager', 'tech_lead']
    - audit: 'drift_alert'

5. Compliance¶

Purpose: Validate regulatory and organizational requirements

Example: HIPAA Compliance for Medical Research¶

policy: hipaa_compliance
  scope: ['content_type: patient_data']
  enforcement: 'blocking'
  requirements:
    # Access controls
    - access_role in ['authorized_researcher', 'pi', 'irb_member']
    - two_factor_auth: true
    
    # Content requirements
    - phi_redacted: true
    - encryption_at_rest: true
    - audit_logging: 'enabled'
    
    # Training requirements
    - hipaa_training_current: true
    - training_expiration_date > now()
    
  rules:
    - no_external_sharing: true
    - require_secure_access: true
    - log_all_access: true
    - retention_period: '7 years'
    
  violation_action:
    - block_access: true
    - notify_immediately: ['compliance_officer', 'privacy_officer', 'pi']
    - incident_report: true
    - audit: 'hipaa_violation'

Example: FDA 21 CFR Part 11 Compliance¶

policy: fda_21cfr11_compliance
  scope: ['regulatory_submission: true']
  enforcement: 'strict_blocking'
  requirements:
    # Electronic signatures
    - electronic_signature_valid: true
    - signature_components:
        - signer_identity_verified: true
        - signature_timestamp: true
        - signature_meaning: 'documented'
    
    # Audit trails
    - audit_trail_complete: true
    - audit_trail_includes:
        - creation_timestamp
        - all_modifications
        - modification_authors
        - deletion_attempts
        - access_logs
    
    # Record integrity
    - content_hash_verified: true
    - tamper_detection: 'enabled'
    - version_control: 'strict'
    
    # System validation
    - system_validated: true
    - validation_documentation: 'complete'
    
  rules:
    - prevent_unaudited_changes: true
    - require_change_reason: true
    - immutable_after_signature: true
    - periodic_audit_review: 'quarterly'
    
  violation_action:
    - block_action: true
    - trigger_deviation_report: true
    - notify: ['quality_assurance', 'regulatory_affairs', 'management']
    - regulatory_incident: true

6. Audit¶

Purpose: Track all decisions with rationale for compliance and accountability

Example: Comprehensive Audit Trail¶

audit_policy: comprehensive_tracking
  track_events:
    # Creation
    - document_created:
        capture: ['author', 'timestamp', 'initial_properties']
    
    # Modifications
    - content_changed:
        capture: ['author', 'timestamp', 'diff', 'change_reason']
    - metadata_changed:
        capture: ['author', 'timestamp', 'old_values', 'new_values']
    - refinement_updated:
        capture: ['old_score', 'new_score', 'rationale']
    
    # Workflow
    - stage_transition:
        capture: ['from_stage', 'to_stage', 'trigger', 'approver']
    - approval_granted:
        capture: ['approver', 'role', 'timestamp', 'conditions_met']
    - approval_denied:
        capture: ['approver', 'role', 'timestamp', 'denial_reason']
    
    # Access
    - document_accessed:
        capture: ['user', 'timestamp', 'access_type']
    - document_exported:
        capture: ['user', 'timestamp', 'format', 'destination']
    
    # Policy violations
    - policy_violation:
        capture: ['policy', 'violation_type', 'attempted_action', 'user']
    - rule_triggered:
        capture: ['rule_name', 'conditions_met', 'actions_taken']
    
  retention:
    default: '7 years'
    regulatory_submissions: 'permanent'
    patient_data: '10 years'
  
  reporting:
    frequency: 'monthly'
    recipients: ['compliance_team', 'management']
    include_metrics: true

Governance at Scale¶

Layer 3 enables governance that scales with document volume:

Scale	Manual Feasibility	Layer 3 Value
100 docs	Manual tracking feasible	Convenient automation
1,000 docs	Dashboards required	Time-saving workflows
10,000 docs	Manual governance breaks	Automation essential
100,000+ docs	Impossible manually	Only viable approach

Example contexts where Layer 3 provides value:

University repositories: Thesis workflows, IRB compliance, embargo management
Pharmaceutical companies: FDA compliance, change control, audit trails
Publishing operations: Editorial calendars, review chains, compliance validation
Research labs: Data sharing policies, consent verification, provenance tracking

The framework provides architectural patterns for these scenarios. Implementation details vary by organization, technology stack, and regulatory requirements.

Why Layer 3 Matters¶

Without Layer 3: Manual governance, inconsistent enforcement, scalability limits

With Layer 3: Automated compliance, consistent policy enforcement, governance at scale

Layer 3 represents the future of knowledge governance at scale. The framework provides architectural patterns and reference specifications—implementations can use any rule engine, workflow system, or policy framework that fits your technology stack.

Next Steps¶

Framework Overview: Return to J-Editorial
Foundations: Review Layer 1 and Layer 2
Practice: See a lightweight Layer 3 implementation in the Case Study
Advanced: The framework documentation covers agentic workflows and orchestration patterns for practitioners ready to integrate agent collaboration.

How Artifacts BEHAVE¶

The Governance Challenge¶

Three Anthropological Axes¶

Circular Axis (Human ↔ Human)¶

Radial Axis (Human ↔ World)¶

Angular Axis (Human ↔ Ideational)¶

Core Capabilities¶

1. Automation¶

Example: Auto-Promote Artifacts¶

Example: Archive Stale Documents¶

2. Enforcement¶

Example: Prevent Publication of Incomplete Work¶

Example: Protect Critical Infrastructure Docs¶

3. Governance¶

Example: Multi-Level Approval Workflow¶

Example: Consent Management for Data Sharing¶

4. Notification¶

Example: Drift Alert for Evergreen Docs¶

5. Compliance¶

Example: HIPAA Compliance for Medical Research¶

Example: FDA 21 CFR Part 11 Compliance¶

6. Audit¶

Example: Comprehensive Audit Trail¶

Governance at Scale¶

Why Layer 3 Matters¶

Next Steps¶