{"id":"W4206395819","doi":"10.1111/nana.12806","title":"Nationalising foreigners: The making of American national identity","year":2022,"lang":"en","type":"article","venue":"Nations and Nationalism","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"University of Essex; Economic and Social Research Council; Russell Sage Foundation","keywords":"Mainstream; Immigration; Leverage (statistics); Ethnic group; National identity; Emigration; Variety (cybernetics); Sociology; Population; State (computer science); Conceptual framework; Identity (music); Gender studies; Political economy; Political science; Politics; Social science; Law; Anthropology; Aesthetics; 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":[0.004567157,0.0001123588,0.0001618653,0.00107936,0.004404943,0.005622561,0.0004207807,0.0004988739,0.002565723],"category_scores_gemma":[0.006470726,0.0001076577,0.00009370916,0.001324627,0.006367458,0.002989793,0.004379693,0.00134798,0.000138478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00124803,"about_ca_system_score_gemma":0.001687777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01161842,"about_ca_topic_score_gemma":0.01918794,"domain_scores_codex":[0.9979104,0.001481962,0.00005132532,0.0001275462,0.0002142356,0.0002145586],"domain_scores_gemma":[0.9975072,0.001239009,0.0004095067,0.0002059903,0.000351891,0.0002865393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000496223,0.00003963273,0.03500031,0.00005362043,0.000008468931,0.0005889535,0.838518,0.00005043984,0.0004807985,0.078949,0.001939353,0.04432172],"study_design_scores_gemma":[0.000003159277,0.00002480013,0.03049169,0.0001777919,0.000007774521,0.0001566875,0.9202521,0.0001160383,0.000197428,0.01020673,0.03834913,0.00001675734],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.915116,0.0005491553,0.0006426255,0.003521066,0.00007172189,0.00001256946,0.00002612032,0.000007328599,0.08005359],"genre_scores_gemma":[0.9982027,0.000292028,0.0001738709,0.0001435233,0.000009452832,0.000003962214,0.00001117309,0.000002486319,0.001160898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01161842,"threshold_uncertainty_score":0.02415377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993852380952566,"score_gpt":0.3610895953254695,"score_spread":0.3311510715159438,"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."}}