{"id":"W2325159763","doi":"10.5117/cms2014.2.volk","title":"Money for Nothing, the Cricks for Free","year":2014,"lang":"en","type":"article","venue":"Comparative Migration Studies","topic":"European Union Policy and Governance","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université de Montréal; Deutscher Akademischer Austauschdienst; European Commission","keywords":"Negotiation; Immigration; Irregular migration; Nothing; Deterrence theory; Immigration policy; Security policy; Political science; Economics; Political economy; Law and economics; Business; Computer security; Economic geography; Law; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002681201,0.0003896072,0.0004237496,0.000902349,0.00578333,0.008809085,0.0006460087,0.003233864,0.01688862],"category_scores_gemma":[0.009201959,0.0002355705,0.0002567035,0.0009598343,0.01462193,0.009637356,0.005887046,0.00417028,0.00323457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002463166,"about_ca_system_score_gemma":0.004085201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005244177,"about_ca_topic_score_gemma":0.007772196,"domain_scores_codex":[0.9972204,0.001317018,0.0001011773,0.0003614916,0.0005515849,0.0004483487],"domain_scores_gemma":[0.9975016,0.0007084709,0.0003420294,0.0004433794,0.0003311565,0.0006734473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000398438,0.00002786787,0.001056455,0.0000729028,0.00001181221,0.0001202853,0.00570333,0.0001160728,0.0001924037,0.8852204,0.07232571,0.0351129],"study_design_scores_gemma":[0.00001253303,0.0000419561,0.001281168,0.0002816435,0.000006310744,0.0002150666,0.007555357,0.0001108952,0.0001498677,0.1059172,0.8844054,0.0000225957],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.04089946,0.006724827,0.008207679,0.2071726,0.00405996,0.00005414702,0.000207656,0.0001419924,0.7325318],"genre_scores_gemma":[0.7170001,0.005525961,0.004565923,0.03314006,0.0006889498,0.0001059348,0.0001562146,0.0001605199,0.2386564],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.01688862,"threshold_uncertainty_score":0.05649805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2331753984749408,"score_gpt":0.4451379713796151,"score_spread":0.2119625729046744,"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."}}