{"id":"W129123389","doi":"10.32920/ryerson.14648688.v1","title":"Attraction and Retention of Immigrants in Small Centres: The Case of Kingston, Ontario","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Immigration; Census; Attraction; Government (linguistics); Local community; Political science; Local government; Geography; Economic growth; Sociology; Public administration; Demography; Economics; Law","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":[0.0007014557,0.0002562873,0.0003814582,0.0007555049,0.0223788,0.003230285,0.001679214,0.0008445294,0.00403608],"category_scores_gemma":[0.001732235,0.0002576239,0.0003591616,0.002237991,0.004806553,0.0008251065,0.003436439,0.0009378569,0.0003320755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05086899,"about_ca_system_score_gemma":0.04960473,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9872494,"about_ca_topic_score_gemma":0.9976701,"domain_scores_codex":[0.9989988,0.0002076904,0.00002365877,0.00007788925,0.0001338119,0.0005580347],"domain_scores_gemma":[0.9982105,0.0002124517,0.0001751352,0.0001007528,0.000462255,0.000838816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002354263,0.0002473571,0.2916752,0.0002578166,0.0000584996,0.0117431,0.6454884,0.0004305069,0.001488634,0.00749122,0.009118323,0.03176556],"study_design_scores_gemma":[0.00001517628,0.00006735877,0.229319,0.0001297097,0.00003559694,0.0007533533,0.7396364,0.0002324189,0.0001660491,0.000343023,0.02926556,0.00003633491],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859464,0.0003288293,0.00007922715,0.001570828,0.00001356085,0.00004662391,0.00009228892,0.000005808958,0.01191649],"genre_scores_gemma":[0.991299,0.0004731396,0.0001560937,0.0002561072,0.000005649718,0.00002145206,0.00005803635,0.000006900001,0.007723597],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05086899,"threshold_uncertainty_score":0.3690821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06508003876439962,"score_gpt":0.2957777725166993,"score_spread":0.2306977337522997,"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."}}