{"id":"W3147667867","doi":"10.1111/imig.12836","title":"Digital media and international migration: Twitter discourse during the Canadian federal election","year":2021,"lang":"en","type":"article","venue":"International Migration","topic":"Social Media and Politics","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Canada","keywords":"Depiction; Social media; Representation (politics); Digital media; Creativity; Public relations; Politics; Political science; Identity (music); Sociology; Federal election; Media studies; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001070481,0.00008739163,0.00006399985,0.00008947467,0.0007310243,0.0008634217,0.0001587586,0.00009161839,0.0003225441],"category_scores_gemma":[0.0006093601,0.00007902016,0.0000501239,0.0001330338,0.0001760522,0.000586625,0.00002473084,0.0001408195,0.00003628781],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004376626,"about_ca_system_score_gemma":0.000430675,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07053416,"about_ca_topic_score_gemma":0.859119,"domain_scores_codex":[0.99894,0.00006840244,0.0001720523,0.0001732735,0.0004464465,0.0001998398],"domain_scores_gemma":[0.999245,0.0001329512,0.00006452548,0.00007060566,0.0003491754,0.000137728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004335114,0.0001042897,0.7852383,0.000006434634,0.000216992,0.00005414589,0.104892,0.00002911914,0.001653967,0.07250482,0.01631029,0.01894636],"study_design_scores_gemma":[0.0007101652,0.00001928597,0.3078758,0.00004748123,0.00002993759,0.00006163362,0.03837266,0.0006489338,0.002184258,0.01253476,0.6370898,0.0004252542],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8707572,0.0000533903,0.0000861416,0.1069215,0.003311494,0.00009723782,0.0000533644,0.00003215555,0.01868746],"genre_scores_gemma":[0.987247,0.00009796528,0.00004315089,0.0007067562,0.002899037,0.00001948999,0.0002435602,0.000008310762,0.008734666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7885848,"threshold_uncertainty_score":0.9356552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02009467393501038,"score_gpt":0.3121642241541508,"score_spread":0.2920695502191405,"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."}}