{"id":"W4244823498","doi":"10.32920/ryerson.14664639","title":"Thinking third sector in Canadian and German settlement and social inclusion","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Labor Movements and Unions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Mitacs","keywords":"German; Settlement (finance); Immigration; Restructuring; Inclusion (mineral); Political science; Welfare state; Context (archaeology); Politics; Immigration policy; Social policy; Economic growth; Economy; Public administration; Political economy; Sociology; Geography; Economics; Social science; Law","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003366394,0.0003256562,0.0003339865,0.004055443,0.01788717,0.01094299,0.001131826,0.001681616,0.004952007],"category_scores_gemma":[0.003688413,0.0001520661,0.0003396502,0.005846675,0.01682291,0.003010001,0.005849187,0.001861819,0.0001583375],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1481113,"about_ca_system_score_gemma":0.1823133,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9775049,"about_ca_topic_score_gemma":0.9902337,"domain_scores_codex":[0.9961309,0.0006889308,0.00006294212,0.0002462688,0.0009013477,0.001969561],"domain_scores_gemma":[0.9979633,0.0004871954,0.0001717413,0.00006232688,0.0006309787,0.000684411],"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":[0.00005317453,0.00003145875,0.01559714,0.0002217322,0.00002054331,0.0004767009,0.1053255,0.0003996674,0.0002230431,0.8097454,0.01490544,0.05300025],"study_design_scores_gemma":[0.00002058306,0.00002923112,0.06532396,0.00149861,0.00005567124,0.0002440433,0.4576284,0.0007064322,0.000554247,0.04809454,0.4257508,0.00009340195],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4422116,0.03735776,0.00168876,0.08166386,0.0006537442,0.00008593751,0.0004069496,0.0000442214,0.4358872],"genre_scores_gemma":[0.978324,0.006216906,0.0005837266,0.002498107,0.00003683133,0.0000177286,0.00007706403,0.00001135568,0.01223425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1481113,"threshold_uncertainty_score":0.9880702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01796431584879565,"score_gpt":0.3063607987044529,"score_spread":0.2883964828556572,"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."}}