{ "design": { "alternatives": [ { "aliasing": "none", "cells": 180, "design_id": "full-180", "estimand_coverage": "complete main effects and interactions", "reason": "infeasible sample and operational burden", "sample_at_32_per_cell": 5760, "selected": false }, { "aliasing": "H7 and H8 contrasts partially aliased", "cells": 16, "design_id": "orthogonal-16", "estimand_coverage": "main effects plus selected interactions", "reason": "fails complete coverage of the eight frozen estimands", "sample_at_32_per_cell": 512, "selected": false }, { "aliasing": "unregistered higher-order interactions remain aliased", "cells": 20, "design_id": "contrast-complete-20", "estimand_coverage": "all eight frozen contrasts plus mechanism and disclosure anchors", "reason": "preserved earlier-version candidate; does not cover all v3 contrasts", "sample_at_32_per_cell": 640, "selected": false }, { "aliasing": "lower than selected design", "cells": 24, "design_id": "expanded-24", "estimand_coverage": "all frozen contrasts plus four robustness anchors", "reason": "no primary-estimand gain over the selected 20-cell design", "sample_at_32_per_cell": 768, "selected": false }, { "aliasing": "unregistered higher-order interactions remain aliased", "cells": 37, "design_id": "threshold-dynamic-37", "estimand_coverage": "all twenty frozen v3 contrasts and versioned anchors", "reason": "bounded additive v3 design covering all registered contrasts", "sample_at_32_per_cell": 1184, "selected": true } ], "analysis_plan": { "cluster": "session", "estimand": "intent-to-treat", "exclusions": [ "duplicate synthetic ID", "assignment outside manifest", "pre-treatment simulator failure" ], "heterogeneity": [ "pre-treatment cost stratum", "round half" ], "manipulation_checks": [ "source choice", "screen visibility", "reward comprehension" ], "missing_data": "retain assignment; missing outcomes remain missing; inverse-probability sensitivity only", "multiplicity": "Holm within each frozen family; power uses conservative Bonferroni family alpha", "per_protocol": "secondary among synthetically compliant records only", "post_treatment_controls": "none in the primary specification", "primary_specification": "outcome on treatment indicator and randomization-block fixed effects", "repeated_rounds": "participant-averaged outcomes, session-clustered inference", "robustness": [ "cluster ICC sensitivity", "attrition sensitivity", "noise sensitivity", "per-protocol secondary" ], "stopping_rule": "fixed registered sample; no outcome-dependent stopping" }, "factor_levels": { "acquisition": [ "free_common", "costly_independent", "assigned_independent" ], "action_horizon": [ "one_shot", "fixed_budget", "stopping" ], "attention_institution": [ "none", "nonbinding_ignore", "license" ], "attribution": [ "absent", "protected" ], "disclosure": [ "private", "public", "public_verifiable" ], "history_visibility": [ "not_dynamic", "hidden", "visible" ], "policy_recommendation": [ "none", "conditional", "contrarian_visible" ], "portfolio_rule": [ "none", "paired_planner", "common_mode", "private_following", "team_tokens", "dynamic_planner" ], "public_access": [ "none", "all", "one_random", "selected_audience", "designated" ], "public_precision": [ "full", "reduced" ], "reward": [ "equal_split", "universal_pooling", "sole_rescue", "marginal_coverage", "dd006b_joint", "team_tokens" ], "team_threshold": [ "none", "two" ], "timing": [ "simultaneous_hidden", "sequential_visible" ] }, "hypotheses": [ { "assumed_effect": 0.2, "control_cell": "T01-costly", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H1", "model": "blocked linear probability model", "multiplicity_family": "acquisition", "outcome": "independent_source_acquisition", "question": "Do participants under-acquire costly independent evidence?", "role": "primary", "treatment_cell": "T02-assigned" }, { "assumed_effect": 0.12, "control_cell": "T00-baseline", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H2", "model": "blocked linear probability model", "multiplicity_family": "information", "outcome": "truthful_report", "question": "Does attribution protection increase truthful disclosure?", "role": "primary", "treatment_cell": "T03-attribution" }, { "assumed_effect": 0.1, "control_cell": "T00-baseline", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H3", "model": "cluster-robust difference in means", "multiplicity_family": "allocation", "outcome": "distinct_informed_actions", "question": "Does public action visibility increase action diversity?", "role": "primary", "treatment_cell": "T06-visible" }, { "assumed_effect": 0.14, "control_cell": "T15-public-pooling", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H4", "model": "cluster-robust linear probability model", "multiplicity_family": "allocation", "outcome": "discovery", "question": "Does allocation repair outperform disclosure alone?", "role": "primary", "treatment_cell": "T19-visible-coverage" }, { "assumed_effect": 0.15, "control_cell": "T07-pooling", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H5", "model": "cluster-robust linear probability model", "multiplicity_family": "allocation", "outcome": "discovery", "question": "Does marginal-coverage reward improve discovery more than universal pooling?", "role": "primary", "treatment_cell": "T09-coverage" }, { "assumed_effect": 0.18, "control_cell": "T05-verifiable", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H6", "model": "blocked linear probability model", "multiplicity_family": "information", "outcome": "action_obedience", "question": "Does the DD-006B mechanism improve joint truth and obedience?", "role": "primary", "treatment_cell": "T16-verifiable-joint" }, { "assumed_effect": 0.1, "control_cell": "T04-public", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H7", "model": "blocked difference in means", "multiplicity_family": "information", "outcome": "disclosure_precision", "question": "Does verifiable provenance improve disclosure precision?", "role": "secondary", "treatment_cell": "T05-verifiable" }, { "assumed_effect": 0.08, "control_cell": "T13-costly-coverage", "direction": "positive", "estimand": "pre-specified difference-in-differences interaction", "hypothesis_id": "H8", "model": "factorial interaction with block fixed effects", "multiplicity_family": "acquisition", "outcome": "social_net_value", "question": "Are acquisition assignment and allocation repair complementary?", "role": "secondary", "treatment_cell": "T14-assigned-coverage" }, { "assumed_effect": 0.22, "control_cell": "T21-random-reader", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H9", "model": "session-clustered difference in means", "multiplicity_family": "attention", "outcome": "public_signal_use", "question": "Does broadcast induce more public-signal use than one-reader access?", "role": "primary", "treatment_cell": "T20-public-all" }, { "assumed_effect": 0.12, "control_cell": "T20-public-all", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H10", "model": "session-clustered linear probability model", "multiplicity_family": "attention", "outcome": "discovery", "question": "Does single-reader access improve discovery relative to full broadcast?", "role": "primary", "treatment_cell": "T21-random-reader" }, { "assumed_effect": 0.18, "control_cell": "T25-ignore-recommendation", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H11", "model": "blocked linear probability model", "multiplicity_family": "implementation", "outcome": "one_reader_alignment", "question": "Does an attention license outperform a nonbinding ignore recommendation?", "role": "primary", "treatment_cell": "T26-attention-license" }, { "assumed_effect": 0.24, "control_cell": "T20-public-all", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H12", "model": "blocked linear probability model", "multiplicity_family": "implementation", "outcome": "one_reader_alignment", "question": "Does a designated reader implement one-reader allocation over broadcast?", "role": "primary", "treatment_cell": "T24-designated-reader" }, { "assumed_effect": 0.08, "control_cell": "T20-public-all", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H13", "model": "session-clustered linear probability model", "multiplicity_family": "attention", "outcome": "discovery", "question": "Do conditional recommendations improve discovery over broadcast?", "role": "secondary", "treatment_cell": "T27-off-signal-rescue" }, { "assumed_effect": 0.07, "control_cell": "T25-ignore-recommendation", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H14", "model": "session-clustered difference in means", "multiplicity_family": "attention", "outcome": "contrarian_action", "question": "Does action visibility induce the registered contrarian response?", "role": "secondary", "treatment_cell": "T28-conditional-visible" }, { "assumed_effect": 0.18, "control_cell": "T30-threshold-common-mode", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H15", "model": "session-clustered linear probability model", "multiplicity_family": "threshold", "outcome": "discovery", "question": "Does paired threshold allocation improve discovery over common-mode crowding?", "role": "primary", "treatment_cell": "T29-threshold-paired-planner" }, { "assumed_effect": 0.14, "control_cell": "T30-threshold-common-mode", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H16", "model": "blocked difference in means", "multiplicity_family": "threshold", "outcome": "threshold_portfolio_efficiency", "question": "Do team-token recommendations improve threshold portfolio efficiency over common mode?", "role": "primary", "treatment_cell": "T32-threshold-team-tokens" }, { "assumed_effect": 0.1, "control_cell": "T30-threshold-common-mode", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H17", "model": "session-clustered difference in means", "multiplicity_family": "threshold", "outcome": "viable_team_count", "question": "Does private following increase viable-team count over common mode?", "role": "secondary", "treatment_cell": "T31-threshold-private-following" }, { "assumed_effect": 0.1, "control_cell": "T34-dynamic-bayes-visible-fixed", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H18", "model": "session-clustered linear probability model", "multiplicity_family": "dynamic", "outcome": "discovery", "question": "Does hidden history preserve discovery relative to visible action history?", "role": "primary", "treatment_cell": "T33-dynamic-bayes-hidden-fixed" }, { "assumed_effect": 0.2, "control_cell": "T35-dynamic-planner-hidden-fixed", "direction": "positive", "estimand": "ITT mean difference", "hypothesis_id": "H19", "model": "blocked difference in means", "multiplicity_family": "dynamic", "outcome": "action_savings", "question": "Does the registered stopping policy save actions relative to a fixed planner horizon?", "role": "primary", "treatment_cell": "T36-dynamic-planner-hidden-stopping" }, { "assumed_effect": 0.16, "control_cell": "T33-dynamic-bayes-hidden-fixed", "direction": "positive", "estimand": "ITT risk difference", "hypothesis_id": "H20", "model": "session-clustered linear probability model", "multiplicity_family": "dynamic", "outcome": "discovery", "question": "Does hidden-history planner allocation improve discovery over hidden-history Bayes behavior?", "role": "secondary", "treatment_cell": "T35-dynamic-planner-hidden-fixed" } ], "no_human_data": true, "notice": "No participants were recruited. No human data were collected. No experiment was conducted. Separate ethics and institutional review are required before deployment.", "outcomes": [ { "definition": "One if the assigned source choice is an independent channel before evidence is observed.", "outcome_id": "independent_source_acquisition", "role": "primary", "unit": "binary" }, { "definition": "One if the submitted report equals the participant's observed synthetic signal.", "outcome_id": "truthful_report", "role": "primary", "unit": "binary" }, { "definition": "One if the action equals the treatment-specific recommendation.", "outcome_id": "action_obedience", "role": "primary", "unit": "binary" }, { "definition": "Distinct evidence-supported actions divided by the team action budget.", "outcome_id": "distinct_informed_actions", "role": "primary", "unit": "team proportion" }, { "definition": "One if at least one team action covers the realized synthetic target.", "outcome_id": "discovery", "role": "primary", "unit": "binary team outcome" }, { "definition": "Team discovery value minus declared source and mechanism costs.", "outcome_id": "social_net_value", "role": "primary", "unit": "expected payoff" }, { "definition": "Number of submitted treatment-permitted messages.", "outcome_id": "communication_volume", "role": "secondary", "unit": "message count" }, { "definition": "Truthful disclosed reports divided by all disclosed reports.", "outcome_id": "disclosure_precision", "role": "secondary", "unit": "proportion" }, { "definition": "Sum of squared action shares within a team-round.", "outcome_id": "action_concentration", "role": "secondary", "unit": "Herfindahl index" }, { "definition": "Sum of squared source-choice shares within a team-round.", "outcome_id": "source_concentration", "role": "secondary", "unit": "Herfindahl index" }, { "definition": "Elapsed synthetic decision time from screen display to submission.", "outcome_id": "response_time", "role": "secondary", "unit": "seconds" }, { "definition": "Pre-specified confidence response submitted before outcome feedback.", "outcome_id": "confidence", "role": "secondary", "unit": "0-100 scale" }, { "definition": "Declared base reward plus transfer minus evidence cost.", "outcome_id": "individual_payoff", "role": "secondary", "unit": "experimental points" }, { "definition": "Total externally financed transfer in a team-round.", "outcome_id": "transfer_budget", "role": "secondary", "unit": "experimental points" }, { "definition": "One if behavior lies in the treatment's frozen exact-model response set.", "outcome_id": "equilibrium_consistent_behavior", "role": "secondary", "unit": "binary" }, { "definition": "Actions using the public clue divided by all submitted actions.", "outcome_id": "public_signal_use", "role": "primary", "unit": "team proportion" }, { "definition": "One when exactly one role conditions its action on the public clue.", "outcome_id": "one_reader_alignment", "role": "primary", "unit": "binary team outcome" }, { "definition": "One when discovery is made by an action differing from the public clue.", "outcome_id": "off_signal_rescue", "role": "secondary", "unit": "binary team outcome" }, { "definition": "Actions choosing the registered third option on clue disagreement.", "outcome_id": "contrarian_action", "role": "secondary", "unit": "team proportion" }, { "definition": "Candidates receiving at least the registered threshold number of actions.", "outcome_id": "viable_team_count", "role": "primary", "unit": "count" }, { "definition": "Realized viable-team discovery divided by the frozen planner value.", "outcome_id": "threshold_portfolio_efficiency", "role": "primary", "unit": "proportion" }, { "definition": "Submitted actions before the fixed horizon or registered stopping time.", "outcome_id": "expected_actions", "role": "secondary", "unit": "action count" }, { "definition": "Fixed action budget minus submitted actions at the registered stopping time.", "outcome_id": "action_savings", "role": "secondary", "unit": "action count" } ], "public_status": "synthetic-preregistration-ready-not-preregistered", "reference_claims": [ "DD-C-0051", "DD-C-0052", "DD-C-0053", "DD-C-0054", "DD-C-0059", "DD-C-0060", "DD-C-0062", "DD-C-0064", "DD-C-0066", "DD-C-0067", "DD-C-0071", "DD-C-0073", "DD-C-0079", "DD-C-0080", "DD-C-0081", "DD-C-0082", "DD-C-0083", "DD-C-0084", "DD-C-0085", "DD-C-0086" ], "reference_runs": [ "20260721T141527Z_DD-008_0d11dc77_7e0c8f1d66", "20260721T163030Z_DD-008A_8b70668b_06307caab4", "20260721T165512Z_DD-006B_f022a1a5_3be21d0b9b", "20260721T171249Z_DD-009_bc78d249_0c3851c41a", "20260721T212943Z_DD-012_9ed0928e_4a3f1ba62b", "20260721T215811Z_DD-013_09c07448_cdac4fb512", "20260721T222047Z_DD-014_f5f099a8_ea0276dd16", "20260722T021526Z_DD-016_00271ff8_123b2809e3", "20260722T043713Z_DD-015_92d53ac1_0e7cf1ec0a", "20260722T044453Z_DD-015_34bc4379_33e1da478b", "20260722T051847Z_DD-018_a193f602_3b3ddac173" ], "response_scenarios": [ { "attrition_rate": 0.0, "effect_multiplier": 1.0, "intracluster_correlation": 0.0, "label": "rational attention equilibrium", "noise_multiplier": 0.85, "scenario_id": "S1-rational" }, { "attrition_rate": 0.0, "effect_multiplier": 0.8, "intracluster_correlation": 0.02, "label": "noisy best response", "noise_multiplier": 1.15, "scenario_id": "S2-quantal" }, { "attrition_rate": 0.0, "effect_multiplier": 0.7, "intracluster_correlation": 0.04, "label": "heterogeneous source costs", "noise_multiplier": 1.1, "scenario_id": "S3-costs" }, { "attrition_rate": 0.0, "effect_multiplier": 0.75, "intracluster_correlation": 0.05, "label": "social preference heterogeneity", "noise_multiplier": 1.2, "scenario_id": "S4-social" }, { "attrition_rate": 0.0, "effect_multiplier": 0.6, "intracluster_correlation": 0.03, "label": "partial compliance", "noise_multiplier": 1.15, "scenario_id": "S5-compliance" }, { "attrition_rate": 0.0, "effect_multiplier": 0.65, "intracluster_correlation": 0.03, "label": "report error", "noise_multiplier": 1.2, "scenario_id": "S6-report-error" }, { "attrition_rate": 0.15, "effect_multiplier": 0.8, "intracluster_correlation": 0.04, "label": "attrition", "noise_multiplier": 1.1, "scenario_id": "S7-attrition" }, { "attrition_rate": 0.05, "effect_multiplier": 0.9, "intracluster_correlation": 0.08, "label": "learning over rounds", "noise_multiplier": 1.05, "scenario_id": "S8-learning" }, { "attrition_rate": 0.0, "effect_multiplier": 0.72, "intracluster_correlation": 0.05, "label": "heterogeneous public-clue salience", "noise_multiplier": 1.18, "scenario_id": "S9-salience" }, { "attrition_rate": 0.0, "effect_multiplier": 0.55, "intracluster_correlation": 0.06, "label": "memory leakage across attention modes", "noise_multiplier": 1.22, "scenario_id": "S10-memory-leakage" }, { "attrition_rate": 0.0, "effect_multiplier": 0.58, "intracluster_correlation": 0.05, "label": "designated-role aversion", "noise_multiplier": 1.2, "scenario_id": "S11-role-aversion" }, { "attrition_rate": 0.0, "effect_multiplier": 0.65, "intracluster_correlation": 0.05, "label": "threshold-team coordination loss", "noise_multiplier": 1.15, "scenario_id": "S12-threshold-coordination" }, { "attrition_rate": 0.0, "effect_multiplier": 0.7, "intracluster_correlation": 0.05, "label": "visible-history herding response", "noise_multiplier": 1.18, "scenario_id": "S13-visibility-herding" }, { "attrition_rate": 0.0, "effect_multiplier": 0.6, "intracluster_correlation": 0.06, "label": "heterogeneous stopping compliance", "noise_multiplier": 1.2, "scenario_id": "S14-stopping-heterogeneity" } ], "schema_version": "dd011-experiment-v3", "study_id": "DD-011", "treatment_cells": [ { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T00-baseline", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "costly_independent", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T01-costly", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "assigned_independent", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T02-assigned", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "protected", "cell_id": "T03-attribution", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T04-public", "disclosure": "public", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T05-verifiable", "disclosure": "public_verifiable", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T06-visible", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "equal_split", "team_threshold": "none", "timing": "sequential_visible" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T07-pooling", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "universal_pooling", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T08-rescue", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "sole_rescue", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T09-coverage", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", "portfolio_rule": "none", "public_access": "none", "public_precision": "full", "reward": "marginal_coverage", "team_threshold": "none", "timing": "simultaneous_hidden" }, { "acquisition": "free_common", "action_horizon": "one_shot", "attention_institution": "none", "attribution": "absent", "cell_id": "T10-joint", "disclosure": "private", "history_visibility": "not_dynamic", "policy_recommendation": "none", 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