{"id":"W3004611522","doi":"10.1080/14494035.2020.1716559","title":"Event-focused network analysis: a case study of anti-corruption networks","year":2020,"lang":"en","type":"article","venue":"Policy and Society","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Network analysis; Social network analysis; Policy transfer; Language change; Event (particle physics); Policy analysis; Computer science; Network theory; Data science; Political science; Public administration; Social media","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":[0.0005787706,0.00009609525,0.0002695883,0.00002930622,0.0006377859,0.00004469069,0.00009712625,0.00009895912,0.00002092834],"category_scores_gemma":[0.00006285029,0.00009410258,0.0002124611,0.001522254,0.0001289724,0.0001008323,0.0000289106,0.0001905947,8.66087e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002291116,"about_ca_system_score_gemma":0.00008364243,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0367633,"about_ca_topic_score_gemma":0.002561415,"domain_scores_codex":[0.9987496,0.0003227739,0.0002160905,0.0001979372,0.0001886599,0.000325012],"domain_scores_gemma":[0.999491,0.0001202951,0.00006515552,0.00009126627,0.00003790936,0.0001943973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001676426,0.0001860245,0.1673431,0.00002274268,0.001025905,0.00004004789,0.7786891,0.0428884,0.00001534467,0.004776713,0.0006042729,0.004391547],"study_design_scores_gemma":[0.004642186,0.001016239,0.2314439,0.00004114009,0.003555935,0.00002162238,0.5792727,0.1687716,0.000007853401,0.000579378,0.009565552,0.001081807],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930675,0.0001321849,0.004391413,0.001180228,0.0000301899,0.0001970217,0.000003317954,0.00005478102,0.0009433643],"genre_scores_gemma":[0.9975524,0.0002176274,0.00006029063,0.001006933,0.001108198,0.000006493042,0.000001871593,0.000007027205,0.00003916769],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1994164,"threshold_uncertainty_score":0.969651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04479976617526985,"score_gpt":0.3523653492373878,"score_spread":0.3075655830621179,"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."}}