{"id":"W1982679242","doi":"10.1017/s0007123414000520","title":"Measuring the Cost of Privacy: A Look at the Distributional Effects of Private Bargaining","year":2015,"lang":"en","type":"article","venue":"British Journal of Political Science","topic":"World Trade Organization Law","field":"Social Sciences","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Transparency (behavior); Negotiation; Parallels; Plaintiff; Disadvantage; Settlement (finance); Business; International trade; Political science; Law; Economics; Law and economics; Finance; Payment","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.004572118,0.00005993613,0.0001636995,0.00003996774,0.0006052019,0.0001188221,0.0009911431,0.00003112026,0.00004300427],"category_scores_gemma":[0.01320448,0.00004260277,0.00006748738,0.0008212554,0.004207557,0.0003538082,0.0002062677,0.0001890791,0.000004410034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004237752,"about_ca_system_score_gemma":0.001226326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005470036,"about_ca_topic_score_gemma":0.00009689228,"domain_scores_codex":[0.9969612,0.0003075649,0.0003979411,0.0001095921,0.001722325,0.000501377],"domain_scores_gemma":[0.9976715,0.0006637627,0.0002908241,0.0001263605,0.0008119119,0.0004356677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000009204865,0.00005916601,0.01386731,0.000008595451,0.00001083507,0.00001698176,0.000924775,0.00002379837,0.001358202,0.9825657,0.0003639557,0.0007914534],"study_design_scores_gemma":[0.001173312,0.0001690469,0.9195666,0.0005765422,0.00007130689,0.0004700432,0.001546031,0.00004631616,0.03750842,0.02993453,0.008735452,0.0002024227],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9809644,0.0003963185,0.001497592,0.01092826,0.000405242,0.0002723745,0.00001634103,0.00001032182,0.005509118],"genre_scores_gemma":[0.9993742,0.00001125934,0.0002194544,0.0001456954,0.0001826684,0.000001003288,3.222011e-7,0.000004587683,0.00006085456],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9526312,"threshold_uncertainty_score":0.9985024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03088014264698934,"score_gpt":0.2910036159213282,"score_spread":0.2601234732743389,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}