{"id":"W4367058111","doi":"10.1257/mic.20210100","title":"Dynamic Privacy Choices","year":2023,"lang":"en","type":"article","venue":"American Economic Journal Microeconomics","topic":"Digital Platforms and Economics","field":"Business, Management and Accounting","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Commit; Privacy policy; Business; Information privacy; Internet privacy; Consumer privacy; Information sensitivity; Outcome (game theory); Personally identifiable information; Computer security; Computer science; Economics; Microeconomics; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.003614752,0.001425476,0.001814465,0.001204151,0.001947271,0.006000918,0.003492431,0.007815309,0.02550362],"category_scores_gemma":[0.01619188,0.001462539,0.001877299,0.002178101,0.003810178,0.008153494,0.003291815,0.006397728,0.002499659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004408996,"about_ca_system_score_gemma":0.00228818,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006858446,"about_ca_topic_score_gemma":0.004858091,"domain_scores_codex":[0.9967408,0.001268089,0.00008531283,0.0007864605,0.0004025243,0.000716792],"domain_scores_gemma":[0.9877308,0.00782789,0.001998824,0.0008191961,0.0005579356,0.001065331],"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":[0.0003186133,0.0003448118,0.003114837,0.0001467017,0.000149264,0.0009049638,0.0004316937,0.1384895,0.0006930311,0.839619,0.006461785,0.009325829],"study_design_scores_gemma":[0.0003950937,0.0002561305,0.001595898,0.00008646974,0.0001030411,0.0004670526,0.0005130778,0.3992068,0.0003463724,0.5826848,0.01422598,0.0001193891],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2460021,0.002259782,0.4936703,0.03164004,0.0004090323,0.0006979393,0.004082036,0.0004866263,0.2207521],"genre_scores_gemma":[0.919283,0.001328733,0.01857265,0.001059894,0.0001824921,0.0004611448,0.0006083438,0.0000667399,0.05843696],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02550362,"threshold_uncertainty_score":0.08531815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013966717170215,"score_gpt":0.220982834508427,"score_spread":0.2108431673367249,"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."}}