{"id":"W2048788123","doi":"10.1002/jae.1052","title":"Do randomized‐response designs eliminate response biases? An empirical study of non‐compliance behavior","year":2009,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministerie van Sociale Zaken en Werkgelegenheid","keywords":"Econometrics; Toolbox; Response bias; Computer science; Multivariate statistics; Randomized response; Statistics; Contrast (vision); Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4272009,0.001085537,0.00271799,0.001974327,0.001321109,0.002556593,0.004688031,0.004356285,0.008012354],"category_scores_gemma":[0.7454994,0.001314969,0.00344664,0.003447128,0.008058442,0.006565798,0.002507159,0.004372274,0.001262026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00204013,"about_ca_system_score_gemma":0.00304382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001099213,"about_ca_topic_score_gemma":0.0005534107,"domain_scores_codex":[0.3030477,0.6605954,0.009884136,0.007604773,0.01696603,0.001901975],"domain_scores_gemma":[0.05109061,0.8646666,0.05193455,0.02723337,0.004676048,0.0003987766],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01416002,0.007453977,0.2284832,0.006982931,0.01113029,0.0008768485,0.01340319,0.02446577,0.001832889,0.2978206,0.009427222,0.3839631],"study_design_scores_gemma":[0.008365746,0.02179744,0.1991889,0.00454215,0.006792594,0.001612774,0.00739118,0.2754406,0.009299979,0.4376713,0.02737054,0.0005267883],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5799915,0.003511213,0.3938469,0.007787325,0.0004997284,0.003470035,0.0006154116,0.0002433901,0.01003441],"genre_scores_gemma":[0.9368144,0.0005368384,0.05765986,0.001299021,0.0002291061,0.002443908,0.0001821843,0.00005251855,0.0007821212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5727991,"threshold_uncertainty_score":0.7063632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3630646595252005,"score_gpt":0.4522586192882325,"score_spread":0.08919395976303202,"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."}}