{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000468613,0.0003172449,0.0005077731,0.0006956434,0.0003058621,0.002352194,0.000736832,0.00005401657,0.0003661799],"category_scores_gemma":[0.00003405625,0.0003375615,0.0002814261,0.0002108218,0.0002198085,0.006451752,0.0003278411,0.000285083,0.0216115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003967981,"about_ca_system_score_gemma":0.00009815164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002984506,"about_ca_topic_score_gemma":0.0002366604,"domain_scores_codex":[0.9980601,0.000001595249,0.0007569951,0.0004063709,0.00004216126,0.000732799],"domain_scores_gemma":[0.9985141,0.00006628553,0.0009783742,0.0003442179,0.00003250987,0.00006447105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003738561,0.0002480913,0.09558386,0.0001700616,0.001138684,0.0001550445,0.0003207879,0.03513621,0.0009622998,0.07644586,0.1408687,0.6485965],"study_design_scores_gemma":[0.001169025,0.0000528026,0.01869478,0.00002815467,0.00005845567,0.000192711,0.00254259,0.04307827,0.00002557611,0.04220685,0.8908281,0.001122724],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9736395,0.00003533773,0.00003828372,0.0009407366,0.001601971,0.0001323593,0.00001383448,0.0002179125,0.02338008],"genre_scores_gemma":[0.993185,0.0004166478,0.0003431753,0.003494243,0.001490502,0.000009593283,0.00006342295,0.0001033695,0.0008940202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7499593,"threshold_uncertainty_score":0.9999076,"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."}}