{"id":"W2981168987","doi":"10.3167/sa.2019.630306","title":"Think Pieces in Analytics","year":2019,"lang":"en","type":"article","venue":"Social Analysis","topic":"Anthropology: Ethics, History, Culture","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mirroring; Scope (computer science); Epistemology; Sociology; Publication; Ethnography; Analytics; Politics; Action (physics); Engineering ethics; Interface (matter); Space (punctuation); Process (computing); Data science; Computer science; Political science; Law; Anthropology; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001032351,0.0001121235,0.000401589,0.0002842817,0.00066444,0.00004498037,0.0003557901,0.0003826132,0.003715146],"category_scores_gemma":[0.0002134651,0.0001108886,0.0003545638,0.002444253,0.0008057692,0.0001547245,0.00004054639,0.0003677674,0.0004829371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003648142,"about_ca_system_score_gemma":0.0002050495,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01790115,"about_ca_topic_score_gemma":0.1742903,"domain_scores_codex":[0.9982267,0.0003746179,0.0002362542,0.0003058962,0.0005012414,0.0003553152],"domain_scores_gemma":[0.9993961,0.00009138243,0.0001427058,0.0001625888,0.0001380566,0.00006912489],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000183475,0.0001688466,0.3181483,0.00001554821,0.001652429,0.00001635317,0.5118786,0.0004277235,0.00003960995,0.1537091,0.01259064,0.001334584],"study_design_scores_gemma":[0.0006550177,0.00004887157,0.1320196,0.00001134991,0.002535564,1.704827e-7,0.5718135,0.000885241,0.00001337691,0.01748537,0.2735768,0.0009550516],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6433353,0.0008231718,0.0003225875,0.03670101,0.001111884,0.0003107846,0.00002806698,0.0002046144,0.3171625],"genre_scores_gemma":[0.9828448,0.0000976983,0.0001130583,0.0005737208,0.0004026412,0.000002104627,0.00001445034,0.000007926767,0.01594366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3395094,"threshold_uncertainty_score":0.9971956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03454742060545896,"score_gpt":0.3642359841590297,"score_spread":0.3296885635535708,"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."}}