{"id":"W2902760328","doi":"10.19173/irrodl.v19i5.3908","title":"User Consent in MOOCs – Micro, Meso, and Macro Perspectives","year":2018,"lang":"en","type":"article","venue":"The International Review of Research in Open and Distributed Learning","topic":"Online Learning and Analytics","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transparency (behavior); Internet privacy; Agency (philosophy); Legislature; Download; Informed consent; Data sharing; Computer science; Data science; World Wide Web; Computer security; Political science; Sociology; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.05084444,0.0003759201,0.0006294373,0.002561931,0.005990057,0.01420499,0.001679673,0.005348226,0.004456365],"category_scores_gemma":[0.0995853,0.0005608128,0.0006232362,0.002397033,0.03240374,0.0152249,0.009443919,0.005751809,0.0005707097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006594056,"about_ca_system_score_gemma":0.01110094,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006528423,"about_ca_topic_score_gemma":0.005529467,"domain_scores_codex":[0.9065745,0.0763291,0.002635542,0.003201052,0.007358745,0.00390108],"domain_scores_gemma":[0.8631201,0.1100493,0.008940497,0.007311908,0.006692937,0.003885326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00009736581,0.0001351347,0.02266545,0.0005458913,0.00005189902,0.0005852932,0.1090377,0.001012261,0.0005557833,0.764196,0.003407415,0.09770984],"study_design_scores_gemma":[0.00004016405,0.0002021397,0.01925671,0.002739969,0.00007419856,0.0008683766,0.113784,0.002483006,0.001602622,0.7021443,0.1566595,0.0001450963],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3079782,0.03548339,0.1311064,0.2320299,0.001099018,0.0007448124,0.0002725529,0.0002324555,0.2910533],"genre_scores_gemma":[0.9863468,0.003341455,0.00313456,0.003326795,0.000281817,0.0001556929,0.00002249627,0.00003764698,0.003352728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05084444,"threshold_uncertainty_score":0.2688943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07460499974563764,"score_gpt":0.4576457354176388,"score_spread":0.3830407356720011,"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."}}