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Orchestrate a deep rewrite of Chapter 2 (Literature Review) using multi-agent pipeline with RAG-backed evidence

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Orchestrate a deep rewrite of Chapter 2 (Literature Review) using multi-agent pipeline with RAG-backed evidence
# Literature Review Rewrite Orchestrator Rewrite Chapter 2 from scratch with deep extraction from ~20 cited papers. Uses a 5-phase pipeline with 7 specialized agents. ## Arguments - `all` — Run the full 5-phase pipeline (default) - `phase1` through `phase5` — Run a specific phase (assumes prior phases completed) - `section N` — Draft only section 2.N (for iterating on one section) ## Workspace All intermediate artifacts go in `thesis/chapters/.litreview_workspace/`. Create it at the start: ```bash mkdir -p /Users/alessandro/Projects/Tesi/thesis/chapters/.litreview_workspace/drafts ``` ## Target Structure (~400-500 lines) ``` Chapter 2: Literature Review ├── Intro paragraph (preview sections using \Cref) ├── 2.1 Automation and the Labor Market │ ├── 2.1.1 The Task-Based Framework │ ├── 2.1.2 Labor Market Polarization │ ├── 2.1.3 Task Displacement and Rent Dissipation │ └── 2.1.4 Bridge paragraph → politics ├── 2.2 Economic Shocks and Political Attitudes │ ├── 2.2.1 The China Shock and Political Consequences │ ├── 2.2.2 Automation and Voting Behavior │ └── 2.2.3 Methodological Parallels (NEW) ├── 2.3 Mechanisms: From Economic Disruption to Political Change │ ├── 2.3.1 The Economic Insecurity Thesis │ ├── 2.3.2 The Cultural Backlash Thesis │ ├── 2.3.3 Status Threat and the 2016 Election │ ├── 2.3.4 Psychological Foundations (DEEPENED) │ └── 2.3.5 Identity Threat as Integrating Framework (NEW) └── 2.4 Contribution of This Thesis ``` --- ## PHASE 1: RESEARCH (parallel) Launch TWO agents in parallel using the Task tool: ### Agent 1: Extraction Assembler (sonnet, read-only) ``` subagent_type: general-purpose model: sonnet ``` **Prompt**: > You are assembling a structured evidence dossier for a thesis literature review rewrite. > > Read ALL files in `thesis/references/literature_analysis/paper_extractions/*.json` (12 files), the concept graph at `thesis/references/literature_analysis/concept_graph.json`, and the mechanism extraction at `thesis/references/literature_analysis/mechanism_extraction.json`. > > Produce TWO JSON files in `thesis/chapters/.litreview_workspace/`: > > **dossier.json** — Organize ALL extracted evidence by the target section structure: > ```json > { > "2.1.1_task_framework": { > "papers": ["autor_levy_murnane_2003"], > "key_quotes": [{"text": "...", "page": N, "bibkey": "autor2003skill"}], > "claims": [{"claim": "...", "evidence": "...", "strength": "strong"}], > "concept_edges": ["task_model → routine_manual", "task_model → substitution"], > "constructs": [{"name": "...", "definition": "..."}] > }, > "2.1.2_polarization": { ... }, > ... > } > ``` > > **gaps.json** — Identify areas where extractions are thin and RAG queries would help: > ```json > { > "gaps": [ > { > "section": "2.1.3", > "topic": "rent dissipation mechanism details", > "query": "rent dissipation automation wage premium loss", > "reason": "Extraction has claim but no detailed mechanism quote" > }, > ... > ] > } > ``` > > Map evidence to these sections: > - 2.1.1: autor_levy_murnane_2003 (task framework, DOT, routine/nonroutine) > - 2.1.2: autor_dorn_2013 (polarization, U-shape, commuting zones, shift-share) > - 2.1.3: acemoglu_restrepo_2025 (task displacement, labor share, rent dissipation) > - 2.2.1: autor_dorn_hanson_majlesi_2020, colantone_stanig_2018 (China shock politics) > - 2.2.2: frey_berger_chen_2018, anelli_colantone_stanig_2019 (robots and voting) > - 2.2.3: methodological parallels (shift-share across studies, pseudo-panel) > - 2.3.1: economic insecurity evidence (Colantone & Stanig, Norris/Inglehart) > - 2.3.2: inglehart_norris_2016, norris_inglehart_2018 (cultural backlash) > - 2.3.3: mutz_2018, morgan_2018 (status threat debate) > - 2.3.4: osborne_2023, stenner_2005 (psychological mechanisms, dual-process) > - 2.3.5: manunta_2025, gidron_hall_2017 (identity threat integration) > - 2.4: contribution positioning > > Include ALL verbatim quotes with page numbers. Be exhaustive — this is the evidence base for the entire chapter. ### Agent 2: RAG Deepener (sonnet, Bash access) ``` subagent_type: general-purpose model: sonnet ``` **Prompt**: > You supplement the literature dossier with additional evidence from the thesis RAG corpus (105 papers, 10,217 chunks in ChromaDB). > > First, if `thesis/chapters/.litreview_workspace/gaps.json` exists, read it and use those queries. If not yet available, use the default queries below. > > For each query, run: > ```bash > cd /Users/alessandro/Projects/Tesi/thesis/references/RAG && source venv/bin/activate && python /Users/alessandro/Projects/Tesi/.claude/skills/verify-claims/scripts/query_rag.py "QUERY" --top-k 5 --json > ``` > > Run 20-30 queries targeting these underdeveloped topics: > > **Section 2.1 (Automation & Labor)**: > 1. "task is routine if can be accomplished by machines following explicit programmed rules" > 2. "Dictionary of Occupational Titles DOT task measures" > 3. "labor market polarization U-shape employment" > 4. "commuting zone shift-share Bartik instrument" > 5. "task displacement labor share decline automation" > 6. "rent dissipation wage premium automation" > 7. "between-group inequality automation 52 percent" > > **Section 2.2 (Shocks & Politics)**: > 8. "China import shock political polarization electoral consequences" > 9. "trade exposure radical right nationalist party Europe" > 10. "economic nationalism protectionism import competition" > 11. "robot exposure Trump presidential election swing states" > 12. "counterfactual occupation assignment automation voting" > 13. "robot exposure distinct from trade exposure" > > **Section 2.3 (Mechanisms)**: > 14. "economic insecurity hypothesis pocketbook egotropic sociotropic" > 15. "cultural backlash silent revolution post-materialist values" > 16. "status threat group dominance racial resentment" > 17. "Morgan critique Mutz 51 vote switchers fixed effects" > 18. "dual-process model RWA SDO authoritarianism" > 19. "authoritarian dynamic normative threat activation" > 20. "identity threat mediates economic cultural populism" > 21. "subjective social status populist right" > 22. "dangerous world belief right-wing authoritarianism" > 23. "competitive jungle social dominance orientation" > > **Section 2.4 (Contribution)**: > 24. "pseudo-panel repeated cross-section Deaton synthetic cohort" > 25. "IRT ideology estimate ideal point continuous measure" > > Save results to `thesis/chapters/.litreview_workspace/rag_supplements.json`: > ```json > { > "queries": [ > { > "query": "...", > "target_section": "2.1.1", > "results": [ > {"source": "Author (Year)", "page": N, "text": "...", "similarity": 0.85} > ] > } > ] > } > ``` > > Prioritize results with similarity > 0.70 that contain verbatim-quotable text with specific numbers, definitions, or methodological details. **Wait for both agents to complete before proceeding to Phase 2.** --- ## PHASE 2: ARCHITECTURE (single agent) ### Agent 3: Narrative Architect (opus) ``` subagent_type: general-purpose model: opus ``` **Prompt**: > You are designing the narrative architecture for a thesis literature review chapter. You have access to: > > 1. Evidence dossier: `thesis/chapters/.litreview_workspace/dossier.json` > 2. RAG supplements: `thesis/chapters/.litreview_workspace/rag_supplements.json` > 3. Current Ch.2: `thesis/chapters/02_literature.tex` (the version being replaced) > 4. Literature synthesis: `thesis/references/literature_analysis/literature_synthesis.md` > 5. Chapter openings for forward refs: > - `thesis/chapters/03_data.tex` (first 30 lines) > - `thesis/chapters/04_methodology.tex` (first 30 lines) > - `thesis/chapters/05_results.tex` (first 30 lines) > > Read all of these files. Then produce `thesis/chapters/.litreview_workspace/outline.md` with this structure: > > ```markdown > # Chapter 2 Outline: Literature Review > > ## Introductory Paragraph > - Preview all four sections using \Cref{sec:lit_automation}, etc. > - ~8-10 lines > > ## Section 2.1: Automation and the Labor Market > \label{sec:lit_automation} > Estimated: ~100-120 lines > > ### 2.1.1 The Task-Based Framework \label{subsec:task_model} > - ~25-30 lines > - Topic sentence: [exact sentence] > - Paper ordering: ALM 2003 only > - Key quotes to include: [list with page numbers] > - Concepts to define: routine vs nonroutine, DOT operationalization, substitution/complementarity > - Forward ref: \Cref{ch:data} (O*NET as modern DOT successor) > - Transition to 2.1.2: [sentence bridging to polarization] > > ### 2.1.2 Labor Market Polarization \label{subsec:polarization} > [same structure...] > > [continue for ALL subsections...] > > ## Citation Plan > | BibTeX key | Sections used | Role (primary/supporting) | > > ## Forward Reference Map > | \Cref target | Section where introduced | Context | > > ## Estimated Total: ~420 lines > ``` > > **Critical requirements**: > - Every subsection must have a specific topic sentence drafted > - Every transition between subsections must be planned > - Every direct quote must be assigned to a specific location with page citation > - The outline must specify which concept graph edges inform each transition > - Section 2.2.3 (Methodological Parallels) is NEW — design it to bridge empirics → your methodology > - Section 2.3.5 (Identity Threat as Integrating Framework) is NEW — must synthesize the mechanisms debate > - Section 2.4 must connect to ALL of Ch.3, Ch.4, Ch.5 > > **DISCURSIVE POSITIONING requirement**: > The literature review must read as a CONVERSATION with other researchers, not a catalog of findings. > For each subsection, the outline must plan at least one "positioning passage" that follows this pattern > (common in top economics journals like QJE, AER, JEPS): > > **Pattern A — "Closely related / distinct from"**: Name 2-3 closest papers → describe what they do > → pivot with "distinct from" / "I depart from" / "unlike" → explain your approach. > Example from Autor et al. (2024, QJE): "Our work is closely related to Webb (2020) and Kogan et al. (2021), > who use NLP tools to identify innovations... Distinct from this literature, we develop a method to..." > > **Pattern B — "While X... I instead..."**: Compare a specific methodological choice by naming what others did > and explaining your alternative. > Example: "While Frey et al. (2018) aggregate robot exposure at the commuting-zone level, and > Anelli et al. (2019) exploit individual-level variation through counterfactual occupation assignment, > I adopt a group-level pseudo-panel..." > > **Pattern C — "Building on X, but extending..."**: Acknowledge what you inherit and add. > Example: "Following the shift-share logic of Autor & Dorn (2013), I aggregate industry-level shocks > to demographic groups using base-year employment weights—but unlike their fixed-baseline approach, > I use rolling windows that capture recent automation dynamics." > > **Pattern D — "None of these studies... This is the gap"**: After reviewing 3-4 related papers, > identify what is missing that your thesis addresses. > > The outline must explicitly mark WHERE each positioning passage goes, using tags like: > `[POSITION: Pattern B — compare Frey CZ-level vs Anelli individual vs my group-level]` > > Key comparisons to plan (at minimum): > - Automation measure: robot counts (A-R 2020) vs RTI proxies (Autor-Dorn) vs task displacement (A-R 2025) → yours > - Unit of analysis: commuting zones (ADH, Frey) vs individual (Anelli) vs demographic groups (yours) > - Political outcome: vote share (Frey, ADHM) vs party ID vs IRT ideology (yours) > - Identification: county-level shift-share (Frey) vs individual counterfactual (Anelli) vs group-level TWFE (yours) > - Geography: US only (Mutz, Frey, ADHM) vs Europe (Colantone-Stanig, Anelli) vs your US state-level > - Temporal design: cross-section (Inglehart-Norris) vs panel (Mutz, Morgan) vs pseudo-panel (yours) > > Write in the voice of a Bocconi Master's student: precise, measured, first person singular. **Wait for completion before Phase 3.** --- ## PHASE 3: DRAFTING (4 parallel agents) Launch FOUR section-drafter agents in parallel using the Task tool. Each writes one `.tex` file. ### Agent 4a-4d: Section Drafters (opus, 4 instances) For each section (2.1, 2.2, 2.3, 2.4), use: ``` subagent_type: general-purpose model: opus ``` **Prompt template** (adjust section number, label, and line target): > You are drafting Section 2.X of the Literature Review chapter for a Bocconi Master's thesis. > > Read these files: > 1. Your section in the outline: `thesis/chapters/.litreview_workspace/outline.md` (Section 2.X only) > 2. Evidence for your section from: `thesis/chapters/.litreview_workspace/dossier.json` (keys starting with "2.X.") > 3. RAG supplements: `thesis/chapters/.litreview_workspace/rag_supplements.json` (entries targeting "2.X.*") > 4. BibTeX file: `thesis/references.bib` (to verify all keys exist) > 5. Notation registry: `.claude/rules/notation-registry.md` > 6. Citation standards: `.claude/rules/literature-citations.md` > 7. Forward reference requirements: `.claude/rules/forward-references.md` > > Write `thesis/chapters/.litreview_workspace/drafts/sec_2.X.tex` containing ONLY the LaTeX content for this section (no `\chapter`, no preamble). > > **Requirements**: > - First person singular: "I review", "I examine", "I identify" > - Present tense for methodology descriptions, past tense for data/findings > - Use `\citet{key}` for author-as-subject, `\citep{key}` for parenthetical > - Every direct quote in `` ``...'' `` must have `\citep[p.~N]{key}`
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