{"id":"W2615558362","doi":"10.1080/21565503.2017.1318759","title":"Beyond disenfranchisement: collateral consequences and equal citizenship","year":2017,"lang":"en","type":"article","venue":"Politics Groups and Identities","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Collateral; Conviction; Citizenship; Scope (computer science); Political science; Democracy; State (computer science); Law and economics; Criminal Conviction; Law; Sociology; 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":[0.003395186,0.0002542378,0.000513264,0.0009425028,0.006669481,0.006555449,0.0009622372,0.001975651,0.007508267],"category_scores_gemma":[0.01355544,0.0001768825,0.0003499497,0.0009418224,0.02824413,0.01008775,0.01012558,0.004442612,0.0002764026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002568866,"about_ca_system_score_gemma":0.002811093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004867378,"about_ca_topic_score_gemma":0.007804014,"domain_scores_codex":[0.9961098,0.001769895,0.0001388346,0.0004870318,0.0006325912,0.0008619505],"domain_scores_gemma":[0.9935666,0.002152524,0.001325728,0.001545586,0.0006775544,0.0007319852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004641825,0.00006705412,0.01138398,0.00003094795,0.0000166627,0.0006378801,0.01893507,0.0003576665,0.0002104085,0.9533187,0.0009916211,0.01400358],"study_design_scores_gemma":[0.00002182132,0.0001328361,0.02257024,0.0003065421,0.00004156056,0.001090204,0.04190107,0.001282199,0.0007310461,0.8955339,0.03633908,0.00004969137],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.66365,0.001116895,0.0183598,0.01643215,0.0001730149,0.00007954371,0.00007280639,0.00003028903,0.3000856],"genre_scores_gemma":[0.9977334,0.0001206187,0.0002299833,0.0002751697,0.00002547134,0.00001353975,0.000008351726,0.000004784444,0.001588646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007508267,"threshold_uncertainty_score":0.0251177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02988507916612165,"score_gpt":0.3191010426798143,"score_spread":0.2892159635136926,"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."}}