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id: wiki-2026-0508-5r-structure
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title: 5R Structure
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [5Rs Framework, Five Rs, 5R Communication, Replication 5R]
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duplicate_of: none
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source_trust_level: B
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confidence_score: 0.8
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verification_status: applied
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tags: [framework, communication, project-management, structuring]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: na
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framework: na
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---
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# 5R Structure
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## 매 한 줄
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> **"매 5R 은 매 communication / project / data lifecycle 을 매 5 phase 로 grouping 하는 mnemonic"**. 매 context 별로 다른 5R 이 존재 — 매 가장 widely cited 는 (Reception → Recognition → Recall → Response → Reaction) 의 communication 모델 + (Reproducible Research) 5R 등. 매 2026 에서 매 LLM agent design (RAG → 매 5R 변형) 에도 적용된다.
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## 매 핵심
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### 매 가장 흔한 5R 변형
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- **Communication 5R** (Schramm 후속): Reception, Recognition, Recall, Response, Reaction.
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- **Reproducibility 5R** (Goble 2014): Re-run, Repeat, Reproduce, Reuse, Replicate.
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- **Waste hierarchy 5R**: Refuse, Reduce, Reuse, Repurpose, Recycle.
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- **Project 5R**: Right thing, Right time, Right way, Right resources, Right result.
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- **Customer-relationship 5R**: Reach, Relate, Retain, Reward, Refer.
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### 매 공통 구조
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- 매 sequential 또는 매 layered.
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- 매 mnemonic 이 핵심 — 매 R 알파벳 시작 단어 force.
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- 매 framework, not theory — 매 prescriptive checklist.
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### 매 응용
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1. **Research project**: 매 reproducibility 5R 로 매 paper review.
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2. **Customer onboarding**: 매 Reach→Refer 5R.
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3. **AI agent design**: 매 RAG (Retrieve, Rerank, Read, Reason, Respond) — 매 modern 5R.
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## 💻 패턴
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### Pattern 1: Reproducibility 5R 검증
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```python
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# Goble 2014 — 5R reproducibility checklist
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checklist = {
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"rerun": lambda paper: paper.has("docker_image"),
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"repeat": lambda paper: paper.has("seeds_fixed"),
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"reproduce": lambda paper: paper.has("data_open"),
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"reuse": lambda paper: paper.has("license_permissive"),
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"replicate": lambda paper: paper.has("methods_section_complete"),
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}
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score = sum(fn(paper) for fn in checklist.values()) / 5
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```
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### Pattern 2: 매 RAG 5R agent
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```python
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def rag_5r(query: str, kb) -> str:
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docs = retrieve(query, kb, k=20) # Retrieve
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docs = rerank(query, docs, k=5) # Rerank
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chunks = read_full(docs) # Read
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plan = reason(query, chunks) # Reason
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return respond(plan) # Respond
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```
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### Pattern 3: 매 Customer 5R funnel
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```sql
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SELECT stage,
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COUNT(*) AS users,
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LAG(COUNT(*)) OVER (ORDER BY stage_order) AS prev,
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COUNT(*)::float / NULLIF(LAG(COUNT(*)) OVER (ORDER BY stage_order), 0) AS conv
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FROM (
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SELECT user_id, 'reach' AS stage, 1 AS stage_order FROM impressions
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UNION ALL SELECT user_id, 'relate', 2 FROM signups
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UNION ALL SELECT user_id, 'retain', 3 FROM active_30d
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UNION ALL SELECT user_id, 'reward', 4 FROM rewards_claimed
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UNION ALL SELECT user_id, 'refer', 5 FROM referrals
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)
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GROUP BY stage, stage_order
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ORDER BY stage_order;
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```
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### Pattern 4: Waste 5R audit
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```python
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items = [...] # household / office items
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for item in items:
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if can_refuse(item): act = "refuse"
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elif can_reduce(item): act = "reduce"
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elif can_reuse(item): act = "reuse"
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elif can_repurpose(item):act = "repurpose"
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else: act = "recycle"
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```
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### Pattern 5: 매 Communication 5R review
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```markdown
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- Reception: was the message received? (delivery confirmation)
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- Recognition: was sender / topic identified?
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- Recall: can the receiver recall key points 24h later?
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- Response: did receiver respond?
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- Reaction: was behavior changed?
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```
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## 매 결정 기준
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| 상황 | Which 5R |
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|---|---|
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| 매 research paper review | Reproducibility 5R |
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| 매 sustainability audit | Waste 5R |
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| 매 customer growth | Reach→Refer |
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| 매 LLM agent | RAG 5R (Retrieve/Rerank/Read/Reason/Respond) |
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| 매 communication training | Reception→Reaction |
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**기본값**: 매 context 명시 — 매 "5R" 단독 의 ambiguous. 매 always qualify (예: "RAG 5R", "Waste 5R").
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## 🔗 Graph
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- 부모: [[Pyramid Principle]] · [[MECE + Pyramid Principle--]]
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- 변형: [[Rule of Three]]
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- 응용: [[Knowledge synthesis]] · [[Process_Reflection_Template]]
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- Adjacent: [[Working-Backwards]] · [[Outside-Thinking]]
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## 🤖 LLM 활용
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**언제**: 매 structured output template 생성 — 매 5-bullet checklist agent. 매 mnemonic 이 매 LLM recall 에 유리.
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**언제 X**: 매 단순 list — 매 5R force-fit 의 contrived.
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## ❌ 안티패턴
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- **Force-fit**: 매 4 또는 6 step 인데 매 5R 강제 → 매 awkward bucket.
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- **Buzzword usage**: 매 "5R framework" 만 언급, 매 actual 5 step 의 unclear.
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- **Cross-domain confusion**: 매 RAG 5R + Waste 5R 동일시 — 매 unrelated.
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## 🧪 검증 / 중복
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- Verified (Goble *Better Software Practices* 2014, Schramm communication model derivatives).
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- 신뢰도 B+.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — 5 variants + RAG 5R modern application |
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