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1{2 "validation_errors": [],3 "repairs": [4  "dropped figures.notes_placeholder_removed"5 ],6 "doc_id": "jof_12696",7 "ontology_version": "1.0",8 "prompt_version": "1.0",9 "model": "claude-opus-5-5",10 "effort": "medium",11 "annotated_at": "2026-11-03T23:26:27+00:00",12 "source_sha256": "69290b0f8b85853098a638f914271cdd1d90690c05130b354115d030f73647a2",13 "parser": "pymupdf-jof-heuristics-1.3",14 "payload_chars": 19268,15 "usage": {16  "input": 6183,17  "output": 2057,18  "cache_read": 3968,19  "cache_write": 020 },21 "cost_usd": 0.066666,22 "request_id": "req_011CggpzR1SNXEjmjWPEQNby",23 "annotation": {24  "genre": "theoretical",25  "subfield": "asset_pricing",26  "subfield_secondary": "financial_intermediation_banking (asset management, search frictions)",27  "primary_method": "theoretical_model_analytical",28  "identification": {29   "estimand": "not applicable (equilibrium comparative statics of market efficiency, fees, and manager performance)",30   "strategy": "Analytical general equilibrium of a Grossman-Stiglitz noisy rational expectations model extended with search for asset managers and Nash-bargained fees",31   "key_assumptions": [32    "costly search for informed managers",33    "costly information acquisition by managers",34    "noise traders and noise allocators",35    "interior equilibrium with investor indifference",36    "linear asset-market equilibrium"37   ],38   "threats_addressed": [],39   "causal_language_strength": 1,40   "uses_causal_claim": false41  },42  "abstract_moves": {43   "question": {44    "present": false,45    "sentence_index": -146   },47   "gap": {48    "present": false,49    "sentence_index": -150   },51   "method": {52    "present": true,53    "sentence_index": 054   },55   "results": {56    "present": true,57    "sentence_index": 158   },59   "magnitude": {60    "present": false,61    "sentence_index": -162   },63   "contribution": {64    "present": false,65    "sentence_index": -166   }67  },68  "introduction": {69   "moves": [70    {71     "paragraph_index": 0,72     "move": "motivation"73    },74    {75     "paragraph_index": 1,76     "move": "preview_of_approach"77    },78    {79     "paragraph_index": 1,80     "move": "preview_of_results"81    },82    {83     "paragraph_index": 2,84     "move": "mechanism_or_theory_sketch"85    },86    {87     "paragraph_index": 3,88     "move": "preview_of_approach"89    },90    {91     "paragraph_index": 4,92     "move": "preview_of_results"93    },94    {95     "paragraph_index": 5,96     "move": "tension_or_puzzle"97    },98    {99     "paragraph_index": 5,100     "move": "related_literature_positioning"101    },102    {103     "paragraph_index": 6,104     "move": "related_literature_positioning"105    },106    {107     "paragraph_index": 7,108     "move": "contribution_statement"109    },110    {111     "paragraph_index": 8,112     "move": "roadmap"113    }114   ],115   "contribution_paragraph_index": 7,116   "contribution_types": [117    "new_theory_or_model",118    "resolution_of_puzzle"119   ],120   "roadmap_present": true,121   "literature_positioning_location": "inside_introduction"122  },123  "section_roles": [124   {125    "idx": 0,126    "role": "introduction"127   },128   {129    "idx": 1,130    "role": "theory"131   },132   {133    "idx": 2,134    "role": "theory"135   },136   {137    "idx": 3,138    "role": "theory"139   },140   {141    "idx": 4,142    "role": "theory"143   },144   {145    "idx": 5,146    "role": "other"147   },148   {149    "idx": 6,150    "role": "conclusion"151   },152   {153    "idx": 7,154    "role": "appendix"155   },156   {157    "idx": 8,158    "role": "appendix"159   }160  ],161  "results_presentation": {162   "economic_significance_discussed": true,163   "statistical_significance_language": "unclear",164   "magnitude_statements_in_intro": true165  },166  "robustness": {167   "location": "appendix",168   "types": [169    "other"170   ]171  },172  "tables": {173   "convention_notes": "The single table is a literature summary that maps model predictions to cited studies and quotes, organized in panels. It reports no estimates.",174   "units_stated_in_notes": false,175   "standard_errors_description": "none"176  },177  "figures": {178   "uncertainty_shown": "no"179  },180  "conclusion": {181   "bounded_claims": false,182   "policy_implications": false,183   "open_questions": false,184   "restates_contribution": true185  },186  "hedging": {187   "level": "low",188   "typical_devices": [189    "'under certain conditions' qualifiers",190    "'consistent with' when linking predictions to evidence",191    "conditional 'if search costs have diminished' framing"192   ]193  },194  "claim_evidence": [195   {196    "claim": "Lower search costs for finding managers raise active allocation, lower fees, and make prices more efficient",197    "evidence_type": "equation_or_proof",198    "evidence_ref": "Section II-III, Figure 3, Appendix A.6"199   },200   {201    "claim": "Informed managers outperform after fees and uninformed managers underperform",202    "evidence_type": "equation_or_proof",203    "evidence_ref": "Proposition 1, Section III.A"204   },205   {206    "claim": "Average manager performance depends on the number of noise allocators and can be zero or negative with free random search",207    "evidence_type": "equation_or_proof",208    "evidence_ref": "Section III.A, Appendix A.2"209   },210   {211    "claim": "Large and sophisticated investors benefit from searching, so managers with such investors outperform",212    "evidence_type": "equation_or_proof",213    "evidence_ref": "Section IV, Appendix A.3"214   },215   {216    "claim": "Cross-sectional manager skill evidence and rising market efficiency are consistent with model predictions",217    "evidence_type": "prior_literature",218    "evidence_ref": "Intro paras 5-6, Section V, Table I"219   },220   {221    "claim": "Market inefficiency magnitude is approximately 6%",222    "evidence_type": "equation_or_proof",223    "evidence_ref": "Section III.C"224   }225  ],226  "structural_summary": "The paper opens by motivating search frictions in asset management and poses questions about efficiency and who outperforms. It then lists numbered predictions and sketches the equilibrium mechanism. Next, it positions the results against puzzles in the mutual fund literature (Fama, Berk-Green) and states its contribution, followed by a roadmap. The body sets up the model, solves the equilibrium, and derives propositions and comparative statics, including a calibrated magnitude. It then extends the model to heterogeneous investors and managers and maps the predictions to existing evidence in a literature table. The conclusion is brief and restates the contribution. Proofs, extensions, and an institutional description of due diligence sit in the appendices.",227  "writing_profile_keywords": [228   "Grossman-Stiglitz extension",229   "search frictions",230   "numbered predictions",231   "tractability emphasis",232   "prediction-to-literature mapping",233   "proposition-based"234  ],235  "confidence": 0.85,236  "notes": "Pure theory paper with an empirical-implications section that relies on prior literature rather than new estimation. Robustness takes the form of model extensions in the appendix (AUM-based search, endogenous noise allocators, partial equilibrium). The 'figures' object contains an extra key not permitted by the schema; the intended value is uncertainty_shown='no'."237 },238 "deterministic_checks": {239  "roadmap_regex": true,240  "contribution_regex_in_intro": false,241  "magnitude_in_abstract": false,242  "abstract_n_sentences": 4,243  "intro_n_paragraphs": 9,244  "intro_n_words": 1121,245  "causal_words_in_abstract": 0,246  "hedge_words_in_abstract": 0,247  "stars_mentioned": false,248  "clustered_se_mentioned": false,249  "internet_appendix_mentioned": false,250  "section_roles_rule": {251   "0": "introduction",252   "1": "theory",253   "2": "theory",254   "3": "theory",255   "4": "other",256   "5": "other",257   "6": "conclusion",258   "7": "appendix",259   "8": "appendix"260  }261 },262 "schema_valid": true,263 "code_version": "87c73cd-dirty"264}
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