{"id":"W2964645011","doi":"10.1177/0306312719865607","title":"Rethinking gaming: The ethical work of optimization in web search engines","year":2019,"lang":"en","type":"article","venue":"Social Studies of Science","topic":"Digital Games and Media","field":"Social Sciences","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University; London School of Economics and Political Science","keywords":"Work (physics); Sociology; Computer science; Search engine; Engineering ethics; Management science; Epistemology; Data science; World Wide Web; Engineering; Philosophy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":["sts"],"domain":null,"study_design":"qualitative","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":["sts"],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003441578,0.00004628455,0.0001526551,0.00006208554,0.0002903764,0.00002777983,0.000406384,0.00006648571,0.00001088692],"category_scores_gemma":[0.001540119,0.00003321697,0.0000376576,0.001521243,0.005432479,0.0001620566,0.0001613012,0.0001803682,0.000002032973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007102365,"about_ca_system_score_gemma":0.0003092146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008551358,"about_ca_topic_score_gemma":0.0002436603,"domain_scores_codex":[0.998566,0.00007510916,0.0001668997,0.0001357589,0.0008101858,0.0002460546],"domain_scores_gemma":[0.9991468,0.0003823482,0.00007744436,0.00006754498,0.0002992114,0.00002670089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001964929,0.00004651857,0.01780381,0.00004726057,0.00001625963,6.232038e-7,0.8563883,0.00263807,0.000614917,0.09146083,0.0001365621,0.03082717],"study_design_scores_gemma":[0.0008635553,0.0002072901,0.04510817,0.0006576229,0.00002614743,2.205687e-7,0.9273782,0.001302076,0.001282613,0.01018095,0.01251078,0.0004823328],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9252078,0.0004308997,0.00001782716,0.00605236,0.0004410626,0.000209451,8.085028e-7,0.00001201801,0.06762778],"genre_scores_gemma":[0.9984698,0.0003208822,0.000388756,0.0000839222,0.0000722103,0.000002715731,1.013562e-7,0.000002348954,0.0006593112],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08127988,"threshold_uncertainty_score":0.9972742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07283206006421261,"score_gpt":0.3738068655660004,"score_spread":0.3009748055017878,"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."}}