{"id":"W3198193544","doi":"","title":"Trends in Human Rights Damages: Courts, Statutory Tribunals and Labour Arbitration","year":2018,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Legal case studies and regulations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Dignity; Adjudication; Human rights; Arbitration; Damages; Jurisdiction; Compensation (psychology); Law; Law and economics; Statutory law; Business; Political science; Economics; Psychology; Social psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02059369,0.0001745275,0.0005114372,0.007857941,0.003807666,0.01275217,0.002254887,0.00549193,0.01084956],"category_scores_gemma":[0.08566102,0.0005705163,0.000608961,0.01481542,0.008165821,0.01257586,0.003166653,0.007344818,0.001296748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02135389,"about_ca_system_score_gemma":0.01259191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08206321,"about_ca_topic_score_gemma":0.1159213,"domain_scores_codex":[0.9794912,0.004885329,0.001784497,0.002112164,0.00930323,0.002423486],"domain_scores_gemma":[0.8992577,0.04853786,0.02746492,0.003182942,0.01807832,0.003478336],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0002106239,0.0001793658,0.09724867,0.0005146968,0.00006738006,0.0005889345,0.01276275,0.001002978,0.0006436235,0.6734744,0.06648815,0.1468185],"study_design_scores_gemma":[0.00005165031,0.0002001398,0.3597493,0.002062401,0.00005796251,0.001435775,0.02591123,0.004136889,0.001684829,0.1166117,0.4878663,0.0002317399],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4424754,0.0757925,0.004642314,0.290453,0.00124838,0.0001376362,0.002245523,0.0001626725,0.1828426],"genre_scores_gemma":[0.9570023,0.0133872,0.001478695,0.01126178,0.0009714355,0.00004885764,0.0007315396,0.0001067189,0.01501149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08206321,"threshold_uncertainty_score":0.1631711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01212978667268875,"score_gpt":0.3146890583346787,"score_spread":0.3025592716619899,"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."}}