{"id":"W2911706576","doi":"10.1177/1077800418806601","title":"The Politics of Gray Data: Digital Methods, Intimate Proximity, and Research Ethics for Work on the “Alt-Right”","year":2019,"lang":"en","type":"article","venue":"Qualitative Inquiry","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Gray (unit); Research ethics; Politics; Sociology; Set (abstract data type); Engineering ethics; Economic Justice; Public relations; Work (physics); Psychology; Political science; Law; Computer science; Engineering; Medicine","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":["metaresearch","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.3625107,0.0009693034,0.001948639,0.006145194,0.02770591,0.0379381,0.004846086,0.01271609,0.005771528],"category_scores_gemma":[0.3251895,0.001415572,0.001310373,0.007616098,0.2479188,0.06064991,0.04039691,0.02685206,0.001177071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01450472,"about_ca_system_score_gemma":0.03552023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004166197,"about_ca_topic_score_gemma":0.005048767,"domain_scores_codex":[0.5472295,0.4089954,0.009186486,0.009755182,0.02131707,0.003516375],"domain_scores_gemma":[0.4308149,0.4876234,0.01090462,0.05251797,0.01138148,0.00675778],"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":[0.00002005382,0.0000244716,0.0005784385,0.0002479105,0.00001687249,0.0001182356,0.0940524,0.0001112828,0.0001275582,0.8855505,0.00248812,0.0166641],"study_design_scores_gemma":[0.00001574002,0.00002968257,0.0002765376,0.001883368,0.00001485175,0.0002802334,0.05876138,0.000303594,0.0003439392,0.8492429,0.08880629,0.00004161636],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02663321,0.02016576,0.3109218,0.5447241,0.003674521,0.0006729822,0.00008938675,0.000183041,0.09293518],"genre_scores_gemma":[0.752066,0.01015002,0.1669502,0.05727021,0.002102717,0.002654686,0.00009022148,0.0004326379,0.00828337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9872839,"threshold_uncertainty_score":0.7861378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5445645352729956,"score_gpt":0.616691327291111,"score_spread":0.07212679201811534,"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."}}