{"id":"W2015464936","doi":"10.1007/s10551-006-9007-7","title":"Marketing Dataveillance and Digital Privacy: Using Theories of Justice to Understand Consumers’ Online Privacy Concerns","year":2006,"lang":"en","type":"article","venue":"Journal of Business Ethics","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":189,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Business ethics; Distributive justice; Privacy by Design; Privacy policy; Consumer privacy; Economic Justice; Business; Quality of Life Research; Internet privacy; Information privacy; Marketing; Privacy software; Public relations; Computer science; Political science; Law","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":[0.02307816,0.0005557278,0.0006813831,0.003327306,0.006769754,0.01606771,0.001930182,0.0101113,0.003362965],"category_scores_gemma":[0.05599625,0.0006558129,0.0009273492,0.002423655,0.05428699,0.02737385,0.005907371,0.01162742,0.0002589182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008009371,"about_ca_system_score_gemma":0.009611567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007660899,"about_ca_topic_score_gemma":0.0075729,"domain_scores_codex":[0.983225,0.01212673,0.0004967033,0.0007810636,0.002253621,0.001116933],"domain_scores_gemma":[0.9161894,0.06775779,0.005645353,0.004682807,0.004171715,0.001552984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001783015,0.00005593774,0.001212103,0.00003543196,0.00001053404,0.00009393878,0.01859623,0.0003287122,0.00006972674,0.9732533,0.001166218,0.005160079],"study_design_scores_gemma":[0.00001352132,0.00001330861,0.0008416735,0.0001287652,0.0000135799,0.0001182762,0.01338432,0.002404877,0.0002410881,0.9730758,0.00974347,0.00002126292],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.182714,0.006182509,0.1794395,0.3748112,0.000580749,0.0001983835,0.00009128968,0.00008203744,0.2559003],"genre_scores_gemma":[0.9822537,0.0008619198,0.008780463,0.005929165,0.000157314,0.00009454918,0.00001640352,0.00003179727,0.001874658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02307816,"threshold_uncertainty_score":0.1220504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1130386436507653,"score_gpt":0.3633313736854891,"score_spread":0.2502927300347239,"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."}}