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1{2 "validation_errors": [],3 "repairs": [4  "dropped hedging.typical_devices_note"5 ],6 "doc_id": "jof_12823",7 "ontology_version": "1.0",8 "prompt_version": "1.0",9 "model": "claude-opus-5-5",10 "effort": "medium",11 "annotated_at": "2026-11-03T23:26:32+00:00",12 "source_sha256": "586ebb40875fdd079c00f469d7ed9f7bd433d038aaec782f2af0734ec8328f02",13 "parser": "pymupdf-jof-heuristics-1.3",14 "payload_chars": 18112,15 "usage": {16  "input": 6147,17  "output": 2203,18  "cache_read": 3968,19  "cache_write": 020 },21 "cost_usd": 0.069442,22 "request_id": "req_011CggqWCDpcyqTTXrKNNrps",23 "annotation": {24  "genre": "mixed_theory_empirical",25  "subfield": "asset_pricing",26  "subfield_secondary": "delegated portfolio management / mutual funds / managerial compensation",27  "primary_method": "reduced_form_regression",28  "identification": {29   "estimand": "How a fund's mid-year distance from its benchmark affects second-half risk-shifting (relative tracking-error volatility), and whether this differs for managers with versus without performance-based contracts",30   "strategy": "Median quantile regressions of the risk adjustment ratio on Distance and excess return. Contract types are hand-collected from SAI filings. Treated funds (performance contracts) are matched to control funds (no performance contracts) on observables. A placebo test randomly reassigns benchmarks.",31   "key_assumptions": [32    "After matching on observables, contract type is uncorrelated with unobservables",33    "The self-designated prospectus benchmark is the relevant compensation benchmark",34    "The ratio of tracking-error volatility captures managerial risk-shifting"35   ],36   "threats_addressed": [37    "selection into contract type on observables",38    "spurious benchmark effects (placebo randomization)",39    "competing flow-performance tournament incentives",40    "managerial ownership, active share and tenure as confounds",41    "alternative risk-shifting measures"42   ],43   "causal_language_strength": 4,44   "uses_causal_claim": true45  },46  "abstract_moves": {47   "question": {48    "present": false,49    "sentence_index": -150   },51   "gap": {52    "present": false,53    "sentence_index": -154   },55   "method": {56    "present": true,57    "sentence_index": 158   },59   "results": {60    "present": true,61    "sentence_index": 262   },63   "magnitude": {64    "present": false,65    "sentence_index": -166   },67   "contribution": {68    "present": true,69    "sentence_index": 370   }71  },72  "introduction": {73   "moves": [74    {75     "paragraph_index": 0,76     "move": "motivation"77    },78    {79     "paragraph_index": 0,80     "move": "literature_gap"81    },82    {83     "paragraph_index": 1,84     "move": "mechanism_or_theory_sketch"85    },86    {87     "paragraph_index": 1,88     "move": "related_literature_positioning"89    },90    {91     "paragraph_index": 2,92     "move": "preview_of_approach"93    },94    {95     "paragraph_index": 2,96     "move": "preview_of_results"97    },98    {99     "paragraph_index": 2,100     "move": "identification_defense"101    },102    {103     "paragraph_index": 3,104     "move": "preview_of_results"105    },106    {107     "paragraph_index": 4,108     "move": "robustness_mention"109    },110    {111     "paragraph_index": 4,112     "move": "contribution_statement"113    },114    {115     "paragraph_index": 4,116     "move": "related_literature_positioning"117    },118    {119     "paragraph_index": 5,120     "move": "related_literature_positioning"121    },122    {123     "paragraph_index": 6,124     "move": "roadmap"125    }126   ],127   "contribution_paragraph_index": 4,128   "contribution_types": [129    "new_evidence",130    "new_data_or_measure",131    "resolution_of_puzzle"132   ],133   "roadmap_present": true,134   "literature_positioning_location": "inside_introduction"135  },136  "section_roles": [137   {138    "idx": 0,139    "role": "introduction"140   },141   {142    "idx": 1,143    "role": "theory"144   },145   {146    "idx": 2,147    "role": "data"148   },149   {150    "idx": 3,151    "role": "results"152   },153   {154    "idx": 4,155    "role": "conclusion"156   },157   {158    "idx": 5,159    "role": "appendix"160   }161  ],162  "results_presentation": {163   "economic_significance_discussed": false,164   "statistical_significance_language": "unclear",165   "magnitude_statements_in_intro": false166  },167  "robustness": {168   "location": "mixed",169   "types": [170    "placebo",171    "alternative_measure",172    "subsample",173    "alternative_specification"174   ]175  },176  "tables": {177   "convention_notes": "Table notes define dependent variables (risk adjustment ratio as a second-half versus first-half tracking-error volatility ratio) and give the quantile-regression specification. Pooled OLS and median quantile regressions are reported side by side. A bootstrap placebo table summarizes 500 benchmark randomizations.",178   "units_stated_in_notes": false,179   "standard_errors_description": "unclear"180  },181  "figures": {182   "uncertainty_shown": "no_figures"183  },184  "conclusion": {185   "bounded_claims": true,186   "policy_implications": false,187   "open_questions": true,188   "restates_contribution": true189  },190  "hedging": {191   "level": "moderate",192   "typical_devices": [193    "'our results suggest'",194    "stating that the contract and tournament channels are not mutually exclusive",195    "declaring agnosticism on contract optimality",196    "explicitly stating the matching assumption"197   ]198  },199  "claim_evidence": [200   {201    "claim": "An asymmetric bonus contract is valued like an exchange option whose vega peaks when the portfolio's return is close to the benchmark's",202    "evidence_type": "equation_or_proof",203    "evidence_ref": "Section I; Appendix A (Margrabe 1978)"204   },205   {206    "claim": "Funds performing closer to the benchmark at mid-year increase relative risk more in the second half",207    "evidence_type": "table",208    "evidence_ref": "Table II"209   },210   {211    "claim": "Risk-shifting is concentrated among funds with a clear compensation benchmark and is absent without performance pay",212    "evidence_type": "table",213    "evidence_ref": "Table III"214   },215   {216    "claim": "Matched treated-control comparison supports a causal effect of contracts on risk-shifting",217    "evidence_type": "table",218    "evidence_ref": "Table IV"219   },220   {221    "claim": "Manager ownership reduces risk-shifting, active share increases it, and tenure mitigates it; Distance remains important",222    "evidence_type": "table",223    "evidence_ref": "Table VI"224   },225   {226    "claim": "Random benchmark assignment does not reproduce the effect",227    "evidence_type": "table",228    "evidence_ref": "Table VII"229   },230   {231    "claim": "The contract-based incentive dominates flow-performance tournament incentives",232    "evidence_type": "table",233    "evidence_ref": "Section III.G"234   }235  ],236  "structural_summary": "The paper opens with an agency-and-contracting motivation, then sketches an option-based theory of the manager's bonus that predicts a hypothesis, priced in the appendix. After describing the data, one long empirical section moves through baseline quantile regressions, hand-collected contract heterogeneity, a matched-sample causal analysis, cross-sectional moderators, a placebo, a horse race against flow incentives, and robustness checks. A brief conclusion bounds the interpretation.",237  "writing_profile_keywords": [238   "option-pricing hypothesis",239   "quantile regression",240   "hand-collected compensation data",241   "matching for causality",242   "placebo bootstrap",243   "tournament versus contract"244  ],245  "confidence": 0.8,246  "notes": "The empirical section is a single large section with robustness checks as subsections, so robustness location is coded as mixed. The theory is light: one hypothesis, with an appendix derivation."247 },248 "deterministic_checks": {249  "roadmap_regex": true,250  "contribution_regex_in_intro": true,251  "magnitude_in_abstract": false,252  "abstract_n_sentences": 4,253  "intro_n_paragraphs": 7,254  "intro_n_words": 953,255  "causal_words_in_abstract": 0,256  "hedge_words_in_abstract": 0,257  "stars_mentioned": false,258  "clustered_se_mentioned": false,259  "internet_appendix_mentioned": false,260  "section_roles_rule": {261   "0": "introduction",262   "1": "theory",263   "2": "data",264   "3": "other",265   "4": "conclusion",266   "5": "appendix"267  }268 },269 "schema_valid": true,270 "code_version": "87c73cd-dirty"271}
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