RTT/Inside Awareness | RTT#
RTT_Inside_module.json— Agentic module schema role assignments
🤖 AI‑Ready Module • TriadicFrameworks
Quick answer: I mapped a concise RTT/Inside lens across 10 broad societal domains, flagged the most common misalignments, and gave short, actionable alignment steps you can capture and expand in your document ✨.
Domains overview and why this matters 🧭#
Below I examine major societal domains as coherent systems of Being, Knowing, and Meaning, then note where attributes often need alignment. I used canonical domain lists and your open project context to shape the scope.
Snapshot comparison table#
| Domain | Core Being | Core Knowing | Core Meaning | Alignment Need |
|---|---|---|---|---|
| Health | patients, providers, systems | clinical evidence, workflows | wellbeing, safety | standardize metadata & lineage |
| Education | learners, curricula, institutions | pedagogy, assessment | learning outcomes | unify competency taxonomies |
| Governance | institutions, laws, agencies | policy, enforcement | public good | clarify accountability chains |
| Economy | firms, markets, money | transactions, models | prosperity, stability | reconcile short/long horizons |
| Infrastructure | assets, networks | engineering, maintenance | service continuity | integrate lifecycle data |
| Environment | ecosystems, resources | monitoring, models | resilience, stewardship | align metrics across scales |
| Technology | platforms, code, devices | protocols, algorithms | capability, trust | surface provenance & intent |
| Culture | communities, media | narratives, norms | identity, cohesion | preserve context in reuse |
| Justice | courts, law enforcement | evidence, procedure | fairness, rule of law | ensure transparent lineage |
| Science & Research | hypotheses, datasets | methods, reproducibility | knowledge growth | enforce reproducible provenance |
Sources: .
Short RTT/Inside notes per domain (brief, emoti‑friendly) 🌟#
- Health: Being = patient state; align clinical metadata so decisions trace to provenance.
- Education: Knowing = assessment signals; align competency labels across systems.
- Governance: Meaning = public mandate; align decision ownership and audit trails.
- Technology: Knowing = algorithmic behavior; align provenance and intent metadata to build trust.
(Repeat pattern as you capture each domain in your doc.)
Key considerations before you capture details ✅#
- Scope: Which subdomains matter first (e.g., primary care vs. pharma)?
- Lineage: Can each domain record who changed what and why?
- Interoperability: Are there shared ontologies or must we create mappings?
- Governance: Who enforces alignment and how will success be measured?
Risks, tradeoffs, and limitations ⚠️#
- Overstandardization can stifle local innovation; balance global schemas with local extensions.
- Data privacy and legal constraints differ by domain and region; alignment must respect them.
- Implementation cost and cultural resistance are real — start with high‑impact, low‑friction pilots.
(These are general system risks; domain specifics will vary and should be captured in your document.)