{"id":"W2624731188","doi":"","title":"Epistemologies in clash: What happens when analytics lands in the organization?","year":2014,"lang":"en","type":"article","venue":"Data Archiving and Networked Services (DANS)","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Analytics; Political science; Data science; Computer science","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":[],"consensus_categories":[],"category_scores_codex":[0.0322882,0.0007670508,0.001237552,0.009761672,0.02063233,0.03488716,0.004517015,0.009707894,0.01886127],"category_scores_gemma":[0.1171888,0.001210337,0.001157546,0.009073815,0.07025101,0.0838796,0.02463073,0.01390314,0.001889195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01282074,"about_ca_system_score_gemma":0.0197163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01579408,"about_ca_topic_score_gemma":0.0125066,"domain_scores_codex":[0.9697379,0.01803357,0.001175932,0.002832344,0.004810419,0.003409867],"domain_scores_gemma":[0.9032074,0.05932622,0.006624941,0.01018162,0.01247232,0.008187477],"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":[0.00006513215,0.00008271851,0.008405084,0.0001302305,0.00003331314,0.0005136426,0.189891,0.00019458,0.0002085096,0.7794735,0.004293228,0.01670902],"study_design_scores_gemma":[0.00002100363,0.00002108371,0.001904976,0.0007236644,0.00002704093,0.0002540508,0.2099602,0.0008850547,0.0003551195,0.7539949,0.03181732,0.00003557084],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3167239,0.00704516,0.08975875,0.2093248,0.00133483,0.0002252558,0.000382968,0.0003652874,0.3748391],"genre_scores_gemma":[0.982359,0.0006755164,0.008433727,0.00366137,0.0001996576,0.00008176087,0.0001660101,0.0002316612,0.004191364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03488716,"threshold_uncertainty_score":0.1707584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05123574822943767,"score_gpt":0.2632727483252174,"score_spread":0.2120370000957797,"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."}}