{"id":"W3140706674","doi":"","title":"Making Sense of the Victim’s Role in Clemency Decision Making","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal principles and applications","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Normative; Order (exchange); Perspective (graphical); Political science; Democracy; Process (computing); Law and economics; Law; Decision-making; Public relations; Sociology; Business; Computer science; 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":[0.03300118,0.0006132392,0.0007792751,0.003334073,0.0160995,0.0192807,0.002618771,0.008235634,0.00730452],"category_scores_gemma":[0.0533917,0.0004079056,0.0006517265,0.001710881,0.04825143,0.01295422,0.0136866,0.007556022,0.0006983305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005436345,"about_ca_system_score_gemma":0.008621069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005656944,"about_ca_topic_score_gemma":0.005363906,"domain_scores_codex":[0.9524792,0.03583988,0.000808311,0.002059057,0.003995636,0.004817887],"domain_scores_gemma":[0.9610826,0.02790748,0.004479425,0.002101494,0.002211685,0.002217239],"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":[0.0000420902,0.00008309964,0.008345305,0.00008084722,0.00003409193,0.001661554,0.299157,0.0003578773,0.0003852329,0.6719662,0.002865338,0.01502147],"study_design_scores_gemma":[0.00002345706,0.0001172634,0.006762332,0.0008457754,0.00004617862,0.001921721,0.5382645,0.001746899,0.001016266,0.3193163,0.1298188,0.000120508],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3900319,0.003074982,0.04173181,0.06044482,0.0005882225,0.0002145602,0.00003141608,0.0000800187,0.5038022],"genre_scores_gemma":[0.9924075,0.0003000291,0.0008739838,0.001897264,0.00006047979,0.00003277697,0.000008385084,0.00001136351,0.004408393],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03300118,"threshold_uncertainty_score":0.174529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0175197173505355,"score_gpt":0.343576910841371,"score_spread":0.3260571934908356,"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."}}