{"id":"W2767376577","doi":"10.1080/08263663.2017.1378381","title":"Land, justice, and memory: challenges for peace in Colombia","year":2017,"lang":"fr","type":"article","venue":"Canadian Journal of Latin American and Caribbean Studies / Revue canadienne des études latino-américaines et caraïbes","topic":"Conflict, Peace, and Violence in Colombia","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia; McGill University","funders":"","keywords":"Impunity; Armed conflict; Economic Justice; Government (linguistics); Context (archaeology); State (computer science); Transitional justice; Political science; Sociology; Development economics; Criminology; Inequality; Political economy; Law; Economic growth; Politics; Economics; Geography","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"],"consensus_categories":["sts"],"category_scores_codex":[0.00208969,0.0005467862,0.001523764,0.0004430556,0.002097553,0.0004077267,0.0006996148,0.0002064352,0.00001421924],"category_scores_gemma":[0.004209021,0.0005698102,0.0002276044,0.0003733572,0.006557678,0.0005405358,0.0001265261,0.0005636193,0.000001452107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009277993,"about_ca_system_score_gemma":0.001242262,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2920558,"about_ca_topic_score_gemma":0.9831751,"domain_scores_codex":[0.9964341,0.000406945,0.0009176435,0.0006125395,0.000190615,0.001438152],"domain_scores_gemma":[0.99407,0.001592666,0.001311162,0.0004505185,0.0009507484,0.001624885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001185121,0.00007898817,0.2291759,0.001932588,0.0008054122,0.0007728441,0.262261,0.00009101804,0.00001681967,0.02601639,0.003090588,0.4756399],"study_design_scores_gemma":[0.001573842,0.0015724,0.3519947,0.00208683,0.0008996871,0.0002068431,0.292088,0.0002441561,0.000003085224,0.001392197,0.3469616,0.0009766868],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8915872,0.07868112,0.000005185515,0.0216462,0.001662417,0.0005195952,0.0002517602,0.00001094942,0.005635601],"genre_scores_gemma":[0.9230406,0.07271111,0.0007120989,0.0004605333,0.0008897851,0.00003616101,0.000004509515,0.00005249687,0.002092701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6911193,"threshold_uncertainty_score":0.9996753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.108507886958401,"score_gpt":0.3380449427771454,"score_spread":0.2295370558187443,"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."}}