Empat Prinsip Inti

Core Principles v2.0

Version 2.0 · · Governance 2.0 public evidence surface

Governance 2.0 Overview

This page is part of the starnum public Governance 2.0 surface and uses the same evidence layer as the system card, data governance, transparency report, use policy, and security policy.

Governance Summary

This page states the operating principles that govern product, content, AI assistance, and public disclosure.

Scope

Cultural respect, autonomy, transparency, privacy, safety, accessibility, and evidence-backed release discipline.

Implementation Status

Version 2.0 turns the principles into a navigation hub connected to the same evidence layer as the policy pages.

Ini adalah kerangka operasional starnum.com.tw. Setiap prinsip memiliki implementasi teknis konkret — bukan sekadar pernyataan.
Terakhir diperbarui:

Prinsip 01
Transparansi Publik
Public & Transparent
Semua informasi yang memengaruhi penilaian pembaca dapat diakses publik; batasan dan ketidakpastian diungkap secara aktif.
Prinsip 02
Dapat Diverifikasi
Verifiable
Setiap klaim memiliki dasar teknis yang dapat diverifikasi secara independen oleh pihak ketiga — tanpa bergantung pada kepercayaan semata.
Prinsip 03
Otoritatif
Authoritative
Klaim didukung oleh literatur, sumber teknis atau akademis yang andal, ditinjau oleh peneliti yang berkualifikasi.
Prinsip 04
Berkelanjutan
Sustainable
Sistem mempertahankan kualitas tinggi jangka panjang dengan input manusia rendah — melalui loop tertutup otomatis, bukan pekerjaan manual.
P1
Transparansi Publik
Public & Transparent
Semua informasi yang memengaruhi penilaian pembaca harus bersifat publik, dapat diakses, dan tidak disembunyikan — sumber pengetahuan, mazhab, batasan yang diketahui, alur tinjauan kualitas, dan setiap perubahan versi. Kami mengungkap kekurangan alih-alih menutupinya.

Implementasi Teknis yang Sudah Ada

P2
Dapat Diverifikasi
Verifiable
Setiap klaim memiliki dasar teknis yang dapat diverifikasi secara independen oleh pihak ketiga. Siapa pun dapat mereproduksi perhitungan kami dengan alat publik; Anda tidak perlu begitu saja percaya.

Implementasi Teknis yang Sudah Ada

P3
Otoritatif
Authoritative
Setiap klaim didukung oleh sumber literatur, teknis, atau akademis yang andal. Kami tidak menerbitkan klaim metafisika tanpa dasar — setiap klaim memiliki sumber pengetahuan yang dapat dilacak, dan konsistensinya dijaga oleh peneliti yang berkualifikasi.

Implementasi Teknis yang Sudah Ada

P4
Berkelanjutan
Sustainable
Sistem mempertahankan kualitas tinggi jangka panjang dengan input manusia rendah. Sistem tidak bergantung pada memori manusia atau pekerjaan manual intensif setiap siklus; loop tertutup berbasis aturan dan otomasi menjaga peningkatan berkelanjutan dan keterawatan.

Implementasi Teknis yang Sudah Ada

Bagaimana Kami Menyelesaikan Konflik Prinsip

Ketika keempat prinsip berkonflik, kami memprioritaskan dengan urutan berikut:

P3 Otoritatif > P1 Transparansi Publik > P2 Dapat Diverifikasi > P4 Berkelanjutan

Dengan kata lain: fitur apa pun yang mengurangi akurasi konten (P3) tidak akan dirilis — bahkan jika meningkatkan transparansi (P1) atau efisiensi (P4).

Contoh Penyelesaian

Matriks Fitur × Prinsip

Setiap fitur inti harus memetakan ke minimal 2 prinsip; jika tidak, kebutuhannya dievaluasi ulang.

Fitur P1 Transparan P2 Verifikasi P3 Otoritatif P4 Berkelanjutan
Hash konten SHA256
Sistem kutipan Claim-Evidence
Audit tata kelola multi-penyedia
Basis pengetahuan Lu Binzhao (KB)
117 aturan keras metafisika
Mesin bagan open-source iztro
Alur kerja kualitas otomatis
Tolok ukur publik (eval-set)
Manajemen siklus hidup aturan

Sumber Transparansi Terkait

Sumber-sumber ini menunjukkan bagaimana empat prinsip diterapkan di setiap lapisan:

Standar eksternal dan sumber primer

Sumber primer berikut menjadi acuan halaman ini. Ini adalah tolok ukur, bukan dukungan pihak ketiga terhadap situs ini.

Current Machine Audit Snapshot

This block uses only traceable local audit data. No unsupported metrics or model claims are added.

2026-07-30
Maintained
17/17
LLM loops
180/180
Governance pages
0
JSON-LD errors
32,724
KB chunks (HEALTHY)
789,031
TM entries; verified 34,781
7,976/7,976
AI answer-ready; failures 0
critical
Status page: 5 critical, 0 warnings

Content Maintenance And Update Decision

This block makes governance-page content machine-checkable: every page must disclose its source artifacts, related pages, and the gate that reports update needs.

Update Decision

This is not static copy. When source artifacts, related policies, public metrics, or generators change, AI Ops reports evidence and an AI agent decides whether the page needs edits.

Human Boundary

Systems detect, report, and preserve machine-readable evidence. Codex/Claude agents perform final judgment and repair.

Verification Command

node scripts/verify-trust-pages.js --check

Verifiable Evidence Layer

This block is not a narrative claim. Each core assertion has a claim id, source JSON, hash, and a repeatable verification command. Public pages disclose governance evidence without exposing source code, secrets, private data, or exploitable attack details.

Claim IDVerifiable valueStatusOwnerSource and verification
claim.public-url-manifest.indexable-count
Public URL and canonical inventory
38,965 indexable URLs verified sitewide node scripts/generate-public-evidence-manifest.js --dry
claim.trust-pages.audit-pass-rate
Trust page machine audit
180/180 pass verified sitewide node scripts/verify-trust-pages.js --check
claim.discovery-surface.zero-errors
AI discovery surface audit
{"errors":0,"warnings":0} verified sitewide node scripts/verify-discovery-surface.js
claim.structured-data.jsonld-errors
JSON-LD / structured data audit
{"structured_data_invalid_files":0,"breadcrumb_count":28274,"faq_count":27506,"dataset_count":30,"article_count":27406} verified sitewide node scripts/site-machine-audit.js
claim.status.sla-state
Status page SLA source
critical / 5 critical, 0 warnings verified sitewide node scripts/generate-status-page.js
claim.provider-alignment.openai-anthropic-gemini
OpenAI / Anthropic / Google Gemini benchmark alignment
benchmark alignment only unless code/config evidence exists verified sitewide node scripts/verify-public-evidence.js --check
claim.transparency-report.sha256
Transparency report SHA-256 anchor
{"report":"transparency/report-2026-Q3.json","sha256":"47b09e2ca4e8b8fe9dffdfaccef3b11212de9ee3a8a14badca8044e2481203c5"} verified sitewide node scripts/update-transparency-current-data.js
claim.release-integrity.gpg-signing
GPG signing status
GPG signing configured locally; GitHub verification pending github_verification_pending sitewide gpg --list-secret-keys --keyid-format=long && git log -1 --show-signature

System Card V2.0: Technical Transparency Layer

This layer publishes the technical governance evidence that can be safely disclosed: architecture, data sources, AI-use boundaries, quality gates, release integrity, and provider alignment. Source code, secrets, exploitable attack details, and private data remain out of scope.

Public architecture

Cloudflare Pages/Workers, R2/D1/KV/Pagefind, and local generation scripts form the public-site and governance publication chain. Public pages disclose behavior, state, and traceable sources, not secrets or internal permissions.

AI-use disclosure

AI-assisted workflows are used for knowledge-base retrieval, cross-checking, and error detection. Governance documents are benchmarked against OpenAI, Anthropic, and Google Gemini public frameworks. Production model usage is disclosed only when code/config evidence exists.

Quality and safety gates

Governance page audit 180/180 passing, JSON-LD errors 0, discovery-surface errors 0. Status pages report critical / 5 critical, 0 warnings as-is.

Data traceability

Knowledge base 32,724 chunks, TM 789,031 entries, AI answer-ready 7,976/7,976. Public metrics trace to data/state-machine/*, data/*audit*.json, and transparency reports.

Governance areaOpenAIAnthropicGoogle GeminiStarnum implementation evidence
Model/system-card disclosureOpenAI models + safety docsClaude model docs + system/model cardsGemini model docs + safety settingssystem-card, model-card, methodology, benchmark, transparency-log
Safety evaluation and use boundariesSafety best practices / deployment checklistResponsible Scaling / safety policyGemini safety controls / policyAI safety, acceptable-use, ethics, risk-boundary copy, crawler policy audit
Data governanceData controls / privacy controlsprivacy and data handling docsGemini API data governance referencesprivacy, ai-data-governance, KB/TM source tracking, SHA-256 hashes
Monitoring and releaseproduction checklist / eval disciplinesystem-card transparency disciplinemodel/version documentation disciplinedeploy.js, status.html, SLA report, trust-pages-machine-audit, sitemap/hreflang audits

The V2.0 goal is not more claims; it separates implemented controls from planned controls. Production usage, benchmark alignment, status exceptions, GPG signing, and SLA breaches are disclosed from source data.

Release Integrity And GPG

GPG signing configured locally. signingkey=0934DFA0EDA6363A. GitHub verification pending until the public key upload and Verified badge are confirmed.

OpenAI / Anthropic / Google Gemini Alignment

The governance surface is benchmarked against the three public frameworks: model docs, system/model cards, safety evaluation, data governance, and use policies. This is benchmark alignment, not a claim that every provider is active in production inference. Official docs checked: 2026-07-30

ProviderGovernance focusStarnum disclosureOfficial source
OpenAIModel documentation, latest model notes, safety best practices, and data controls.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://platform.openai.com/docs/models
AnthropicClaude model documentation, system/model cards, Responsible Scaling, and safety policy.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://docs.anthropic.com/en/docs/about-claude/models
Google GeminiGemini API model documentation, safety settings, data governance, and platform policy.No verifiable production model setting was found in the production code scan; providers are listed as governance benchmarks.https://ai.google.dev/gemini-api/docs/models