{"id":"W2898230640","doi":"10.1177/2053951718805214","title":"Children’s digital playgrounds as data assemblages: Problematics of privacy, personalization, and promotional culture","year":2018,"lang":"en","type":"article","venue":"Big Data & Society","topic":"Child Development and Digital Technology","field":"Social Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Brock University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Personalization; Internet privacy; Analytics; Digital media; Social media; Computer science; TRACE (psycholinguistics); The Internet; World Wide Web; Advertising; Sociology; Business; Data science","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":[],"consensus_categories":[],"category_scores_codex":[0.0004717495,0.000122684,0.0001592585,0.00002135483,0.0003968117,0.0002688267,0.001350607,0.0001732828,0.00003156881],"category_scores_gemma":[0.0006208623,0.0001077442,0.00002964155,0.0003255728,0.0008292056,0.00137737,0.001564563,0.00009500355,0.00001772398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003734021,"about_ca_system_score_gemma":0.0003707023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008729767,"about_ca_topic_score_gemma":0.0001737165,"domain_scores_codex":[0.9985926,0.00002363899,0.0002439028,0.0004545504,0.0004650106,0.0002202731],"domain_scores_gemma":[0.9988087,0.00004618563,0.0001518034,0.0007645866,0.0001549922,0.00007373161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001573355,0.0006395956,0.137159,0.000174939,0.0004159114,0.000001488111,0.09047578,6.230979e-8,0.0001584096,0.05314581,0.6911895,0.02662375],"study_design_scores_gemma":[0.002215971,0.0003818417,0.1095621,0.0003862597,0.000173337,0.00006658267,0.03012674,0.0006807838,0.0002124018,0.04741796,0.8074084,0.001367638],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9427904,0.001018136,0.01035881,0.006604055,0.0006051199,0.00173846,0.005427176,0.0005701662,0.03088769],"genre_scores_gemma":[0.9879153,0.0003895103,0.003195578,0.0001592035,0.0005743341,0.000003861014,0.006803812,0.00001246407,0.0009459684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1162189,"threshold_uncertainty_score":0.4393681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.103679091322797,"score_gpt":0.3340405123595719,"score_spread":0.2303614210367749,"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."}}