{"id":"W2143148446","doi":"10.7202/037917ar","title":"Volunteering, Income Support Programs and Persons with Disabilities","year":2009,"lang":"en","type":"article","venue":"Relations industrielles","topic":"Nonprofit Sector and Volunteering","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Compensation (psychology); Unpaid work; Volunteer work; Income Support; Work (physics); Relevance (law); Principal (computer security); Incentive; Disability insurance; Demographic economics; Actuarial science; Psychology; Public relations; Business; Political science; Social psychology; Economics; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001964797,0.00009798419,0.000104554,0.00006432549,0.0006110857,0.0001004606,0.00009248493,0.0001393335,0.0001962637],"category_scores_gemma":[0.0001201082,0.00008662249,0.00002582809,0.0003074884,0.0003246758,0.0002697048,0.00001471944,0.0002247507,0.00001450388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007505692,"about_ca_system_score_gemma":0.0001476784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009266352,"about_ca_topic_score_gemma":0.0009579535,"domain_scores_codex":[0.9992039,0.00003976023,0.0001238064,0.0001706483,0.0002039223,0.0002580143],"domain_scores_gemma":[0.9996018,0.00008504241,0.00003715354,0.0001192895,0.00004087396,0.0001158764],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008311979,0.00004774343,0.9198802,0.000001461305,0.00001600417,0.000002491225,0.02917909,0.00001634693,0.00001479121,0.03191985,0.0005881319,0.01832566],"study_design_scores_gemma":[0.0008914467,0.0008793192,0.3761454,0.0002094703,0.0000985981,0.00002334345,0.183895,0.0002058035,0.00009252047,0.002118628,0.4345884,0.0008520484],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9454514,0.0001020245,0.0001741783,0.001738573,0.00005780373,0.0002618358,0.000003391409,0.0001656213,0.05204517],"genre_scores_gemma":[0.9885035,0.00001943112,0.0004491177,0.00002357275,0.0001336433,0.00001327181,0.000006587584,0.000008003118,0.01084293],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5437347,"threshold_uncertainty_score":0.4700039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03006518671450749,"score_gpt":0.2840528116237095,"score_spread":0.253987624909202,"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."}}