Diff: governance/ontological-governance
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| schema: foundry-doc-v1 | schema: foundry-doc-v1 |
| title: "Ontological governance" | title: "Ontological governance" |
| slug: ontological-governance | slug: ontological-governance |
| category: governance | category: governance |
| type: topic | type: topic |
| quality: complete | quality: complete |
| short_description: "Ontological governance describes the four self-healing control ledgers that govern how service-content classifies and accumulates knowledge, and the human-verification loop that keeps extracted identity data accurate before it is permanently committed." | short_description: "Ontological governance describes the four self-healing control ledgers that govern how service-content classifies and accumulates knowledge, and the human-verification loop that keeps extracted identity data accurate before it is permanently committed." |
| status: active | status: active |
| bcsc_class: public-disclosure-safe | bcsc_class: public-disclosure-safe |
| last_edited: 2026-05-19 | last_edited: 2026-05-19 |
| editor: pointsav-engineering | editor: pointsav-engineering |
| cites: [] | cites: [] |
| paired_with: ontological-governance.es.md | paired_with: ontological-governance.es.md |
| --- | --- |
| Automated classification systems drift over time — categories multiply, vocabulary fractures, and extracted data accumulates errors faster than they can be corrected. **Ontological governance** prevents this through two structural mechanisms: four throttled control ledgers that define classification vocabulary at intentionally slow update rates, and a human-verification loop that forces extracted identity fragments through human review before they are permanently written into the verified ledger. These two mechanisms are structurally separate but serve the same goal: preventing accumulated classification drift from undermining the integrity of long-lived institutional data. For a regulated operator, this means the platform's knowledge graph remains auditable and its identity records remain accurate without continuous manual curation. | Automated classification systems drift over time — categories multiply, vocabulary fractures, and extracted data accumulates errors faster than they can be corrected. **Ontological governance** prevents this through two structural mechanisms: four throttled control ledgers that define classification vocabulary at intentionally slow update rates, and a human-verification loop that forces extracted identity fragments through human review before they are permanently written into the verified ledger. These two mechanisms are structurally separate but serve the same goal: preventing accumulated classification drift from undermining the integrity of long-lived institutional data. For a regulated operator, this means the platform's knowledge graph remains auditable and its identity records remain accurate without continuous manual curation. |
| ## The three-stage extraction pipeline | ## The three-stage extraction pipeline |
| Data extraction across the platform is mechanically isolated into | Data extraction across the platform is mechanically isolated into |
| three services: | three services: |
| 1. **[[service-email]] (ingestion).** Processes MIME payloads and | 1. **[[service-email]] (ingestion).** Processes MIME payloads and |
| deposits raw text and CSV files into the spool. No | deposits raw text and CSV files into the spool. No |
| classification is applied at this stage. | classification is applied at this stage. |
| 2. **[[service-people]] (identity resolution).** Scans the spool | 2. **[[service-people]] (identity resolution).** Scans the spool |
| for human identity clusters and routes them to the verification | for human identity clusters and routes them to the verification |
| surveyor before committing to the verified ledger. | surveyor before committing to the verified ledger. |
| 3. **[[service-content]] (linguistic classification).** Scans the | 3. **[[service-content]] (linguistic classification).** Scans the |
| spool for narrative knowledge and cross-references text against | spool for narrative knowledge and cross-references text against |
| the four control ledgers. | the four control ledgers. |
| ## The four control ledgers | ## The four control ledgers |
| `service-content` is governed by four CSV ledgers that update at | `service-content` is governed by four CSV ledgers that update at |
| heavily throttled rates to preserve longitudinal data stability: | heavily throttled rates to preserve longitudinal data stability: |
| | Ledger | Minimum update interval | Governs | | | Ledger | Minimum update interval | Governs | |
| |---|---|---| | |---|---|---| |
| | [[archetypes-and-chart-of-accounts|Archetypes]] | More than 24 months | The psychological and functional identity of the firm (for example, "The Fiduciary") | | | [[archetypes-and-chart-of-accounts|Archetypes]] | More than 24 months | The psychological and functional identity of the firm (for example, "The Fiduciary") | |
| | [[archetypes-and-chart-of-accounts|Chart of Accounts]] | 18–24 months; requires executive override | The structural and financial geometry of the operation (for example, "Compliance", "IT Support") | | | [[archetypes-and-chart-of-accounts|Chart of Accounts]] | 18–24 months; requires executive override | The structural and financial geometry of the operation (for example, "Compliance", "IT Support") | |
| | Domains | More than 12 months | Bilingual glossaries defining the macro-categories: Corporate (Finance), Projects (Real Estate), Documentation (Technology) | | | Domains | More than 12 months | Bilingual glossaries defining the macro-categories: Corporate (Finance), Projects (Real Estate), Documentation (Technology) | |
| | Themes | 3–8 months | The active frontline narratives (for example, "Co-Location Expansion") | | | Themes | 3–8 months | The active frontline narratives (for example, "Co-Location Expansion") | |
| Update rates are intentionally asymmetric. The slowest ledgers | Update rates are intentionally asymmetric. The slowest ledgers |
| (Archetypes, Chart of Accounts) capture what the firm fundamentally | (Archetypes, Chart of Accounts) capture what the firm fundamentally |
| is; the fastest (Themes) capture what it is currently working on. | is; the fastest (Themes) capture what it is currently working on. |
| Premature updates to the slower ledgers corrupt the longitudinal | Premature updates to the slower ledgers corrupt the longitudinal |
| coherence of the data corpus. | coherence of the data corpus. |
| ## The verification loop | ## The verification loop |
| `service-people` uses a human-in-the-loop verification step to prevent automated extraction errors from entering the verified ledger. The process is described in detail at [[verification-surveyor|Verification Surveyor]]. In brief: the system isolates unverified identity fragments for operator review; the operator verifies each entity using their own personal browser and off-network lookup; the verified result is then committed to the ledger. The daily throughput limit ensures that operator attention remains high-fidelity rather than habitual. | `service-people` uses a human-in-the-loop verification step to prevent automated extraction errors from entering the verified ledger. The process is described in detail at [[verification-surveyor|Verification Surveyor]]. In brief: the system isolates unverified identity fragments for operator review; the operator verifies each entity using their own personal browser and off-network lookup; the verified result is then committed to the ledger. The daily throughput limit ensures that operator attention remains high-fidelity rather than habitual. |
| ## Why asymmetric update rates matter for regulated operators | ## Why asymmetric update rates matter for regulated operators |
| The asymmetric ledger structure produces a property that matters in regulated contexts: the base of the knowledge graph is stable enough to audit. A procurement evaluator or compliance reviewer reading data extracted two years ago and data extracted last week will find them classified against the same Archetypes and Chart of Accounts taxonomy — the categories have not drifted. Only the Themes layer, which updates most frequently, reflects the current operational focus. | The asymmetric ledger structure produces a property that matters in regulated contexts: the base of the knowledge graph is stable enough to audit. A procurement evaluator or compliance reviewer reading data extracted two years ago and data extracted last week will find them classified against the same Archetypes and Chart of Accounts taxonomy — the categories have not drifted. Only the Themes layer, which updates most frequently, reflects the current operational focus. |
| For financial disclosure purposes, this means that the platform's knowledge graph does not introduce spurious variation into the record. Consistent classification over time is not a side effect of discipline; it is a structural property enforced by the update-rate ledger. An auditor querying "what has this firm classified as Compliance over the past three years" receives a meaningful answer because the category boundaries have not shifted underneath the data. | For financial disclosure purposes, this means that the platform's knowledge graph does not introduce spurious variation into the record. Consistent classification over time is not a side effect of discipline; it is a structural property enforced by the update-rate ledger. An auditor querying "what has this firm classified as Compliance over the past three years" receives a meaningful answer because the category boundaries have not shifted underneath the data. |
| ## See also | ## See also |
| - [[verification-surveyor|Verification Surveyor]] — the human-in-the-loop agent that verifies identity fragments before they enter the ledger | - [[verification-surveyor|Verification Surveyor]] — the human-in-the-loop agent that verifies identity fragments before they enter the ledger |
| - [[archetypes-and-chart-of-accounts]] — the two slowest-updating control ledgers that define firm identity and financial geometry | - [[archetypes-and-chart-of-accounts]] — the two slowest-updating control ledgers that define firm identity and financial geometry |
| - [[message-courier|Message Courier Service]] — the routing substrate that delivers inbound communications to service-email | - [[message-courier|Message Courier Service]] — the routing substrate that delivers inbound communications to service-email |
| - [[moonshot-initiatives|Moonshot Initiatives]] — engineering program to replace quarantined dependencies that ontological governance depends on | - [[moonshot-initiatives|Moonshot Initiatives]] — engineering program to replace quarantined dependencies that ontological governance depends on |
| - [[worm-ledger-design]] — the append-only storage substrate that makes the verified ledger authoritative | - [[worm-ledger-design]] — the append-only storage substrate that makes the verified ledger authoritative |