{"id":"W2794047183","doi":"10.26481/dis.20180328fp","title":"The citizenship premium","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Council on Foreign Relations","funders":"","keywords":"Naturalisation; Citizenship; Context (archaeology); Immigration; Settlement (finance); Political science; Development economics; Economics; Geography; Law; Politics","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":[0.0008916364,0.00009604057,0.0002723384,0.0006941282,0.0005799601,0.003322202,0.0002221446,0.0005210499,0.02636013],"category_scores_gemma":[0.006804209,0.00008142991,0.0001981912,0.001235632,0.000992729,0.001618608,0.001007636,0.0008754135,0.0009527376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138936,"about_ca_system_score_gemma":0.001001739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006787232,"about_ca_topic_score_gemma":0.008592838,"domain_scores_codex":[0.9990971,0.000216435,0.00004339629,0.0001540582,0.0002674258,0.0002216428],"domain_scores_gemma":[0.9976056,0.001353669,0.0003184371,0.0002141993,0.0002522602,0.0002558618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003746605,0.0001000306,0.06972291,0.00008155641,0.00002944777,0.0002383665,0.003738828,0.0008335685,0.0003607911,0.8627863,0.01199841,0.05007226],"study_design_scores_gemma":[0.00003126854,0.0000941589,0.3773257,0.0003805958,0.00005847496,0.0005156072,0.01148483,0.004685417,0.000792849,0.4451775,0.1594082,0.0000454037],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5164729,0.002646995,0.003745118,0.01078169,0.0001446391,0.00006009139,0.001875615,0.00003712816,0.4642358],"genre_scores_gemma":[0.9784667,0.0005948131,0.0002906572,0.000151909,0.00009782333,0.0000192836,0.0002513021,0.000009367929,0.02011809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02636013,"threshold_uncertainty_score":0.0881834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0160273347910249,"score_gpt":0.3245607025212639,"score_spread":0.308533367730239,"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."}}