{"id":"W1567018564","doi":"10.21057/repam.v3i1.1365","title":"NAFTA refugees as protagonists: mexican migrant workers take on the fast food giants","year":2009,"lang":"en","type":"article","venue":"Revista de Estudos e Pesquisas sobre as Américas","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Refugee; Migrant workers; Food processing; Production (economics); Business; Agricultural economics; Advertising; Food science; Political science; Economic growth; Economics; Biology; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00182598,0.0005680811,0.0007574889,0.0002216207,0.003623686,0.0001442493,0.0009231357,0.0004427957,0.0009824563],"category_scores_gemma":[0.001505228,0.00042303,0.000310533,0.0009960481,0.000237171,0.0001775438,0.0001851802,0.001982107,0.002707746],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007200876,"about_ca_system_score_gemma":0.001155091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006317793,"about_ca_topic_score_gemma":0.0003871788,"domain_scores_codex":[0.9939661,0.001373522,0.001242468,0.0008193142,0.0008961164,0.00170245],"domain_scores_gemma":[0.9961121,0.0008633736,0.0006792166,0.001351561,0.0002962017,0.0006975143],"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":[0.001582885,0.001959321,0.04758165,0.001029605,0.0004499153,0.0002270406,0.04249372,0.00007668241,0.0001405094,0.6289306,0.2604895,0.01503859],"study_design_scores_gemma":[0.001512444,0.00268572,0.06469529,0.001819963,0.0001641534,0.00004802813,0.01325445,0.0001369882,0.00002604105,0.007862086,0.9069821,0.0008127004],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7958577,0.001355061,0.00006054818,0.09696604,0.0007729302,0.007523586,0.0002279639,0.0006615056,0.09657471],"genre_scores_gemma":[0.9803028,0.000191385,0.000347134,0.01463145,0.0007499374,0.0005274328,0.00006331602,0.00007005374,0.003116539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6464926,"threshold_uncertainty_score":0.9999308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08196407601493844,"score_gpt":0.4179562960774234,"score_spread":0.335992220062485,"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."}}