{"id":"W3126007474","doi":"10.1257/aer.102.3.349","title":"Shifts in Privacy Concerns","year":2012,"lang":"en","type":"article","venue":"American Economic Review","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":278,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Queen's University","keywords":"Digitization; Information privacy; Perception; Internet privacy; Privacy policy; Marketing; Personally identifiable information; Business; Survey data collection; Measure (data warehouse); Economics; Advertising; Psychology; Political science; Computer science; Law; Telecommunications; Data mining","routes":{"ca_aff":true,"ca_fund":true,"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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001175358,0.00008810831,0.0003065514,0.00003891867,0.0000968029,0.00002500631,0.0004198963,0.00002437187,0.0005580112],"category_scores_gemma":[0.0003942219,0.00009000982,0.00006240427,0.0001587485,0.0002755853,0.0005688735,0.000122945,0.0001052528,0.001041561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000305203,"about_ca_system_score_gemma":0.0001279124,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01333078,"about_ca_topic_score_gemma":0.001843586,"domain_scores_codex":[0.9988573,0.0002680138,0.0002744175,0.0001732446,0.0000669658,0.0003600942],"domain_scores_gemma":[0.9992428,0.0000719435,0.0001966222,0.0003359426,0.000007910211,0.0001447758],"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":[0.0000071519,0.00009981213,0.09477284,0.000272941,0.00002284525,0.000001311098,0.006085867,4.704273e-7,0.000005246367,0.02963881,0.03344408,0.8356486],"study_design_scores_gemma":[0.00007346431,0.00001438382,0.0195659,0.0001696711,0.000009867663,5.432295e-7,0.00039532,0.000002459528,0.000002744488,0.0005437104,0.9790853,0.0001366769],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.434492,0.2681982,0.0002624661,0.0356394,0.002694531,0.003619864,0.00005904512,0.0003337668,0.2547008],"genre_scores_gemma":[0.8214751,0.1757047,0.0002065103,0.001985663,0.0004867963,0.00006082972,0.000007117385,0.000008682501,0.00006452535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9456412,"threshold_uncertainty_score":0.9997362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05354732880267764,"score_gpt":0.3609880748091749,"score_spread":0.3074407460064973,"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."}}