{"id":"W2558445914","doi":"10.1111/imre.12310","title":"Selections Before the Selection: Earnings Advantages of Immigrants Who Were Former Skilled Temporary Foreign Workers in Canada","year":2016,"lang":"en","type":"article","venue":"International Migration Review","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Immigration; Earnings; Demographic economics; Earnings growth; Labour economics; Economics; Political science; 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":[0.000594949,0.0001472313,0.0002230599,0.0008925828,0.001654236,0.001079855,0.0004418022,0.0002831903,0.001974481],"category_scores_gemma":[0.001319474,0.00006615572,0.0002590194,0.001928363,0.0005642304,0.0002414304,0.0004736252,0.0003569895,0.0001431191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007140638,"about_ca_system_score_gemma":0.0202008,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9494288,"about_ca_topic_score_gemma":0.9788545,"domain_scores_codex":[0.999651,0.0000297945,0.0000107556,0.00002841342,0.0001030525,0.0001770608],"domain_scores_gemma":[0.9994973,0.00004915455,0.00009427504,0.000009078848,0.0001967621,0.0001534397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006734779,0.0001498288,0.6654842,0.0008956952,0.0001608006,0.001623436,0.008637931,0.0003716566,0.0008044437,0.004521696,0.008831793,0.307845],"study_design_scores_gemma":[0.00001456371,0.0000485611,0.9704821,0.0005117347,0.00008136427,0.0002688143,0.0080724,0.00008087526,0.000123893,0.0002341916,0.02006441,0.00001713084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8994678,0.07855607,0.00008977057,0.00245627,0.0001363326,0.00001855393,0.0006546934,0.000005638424,0.01861486],"genre_scores_gemma":[0.9391953,0.05482375,0.00009263244,0.0003112895,0.00006372111,0.000005632307,0.0004396153,0.000003587672,0.005064474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0505712,"threshold_uncertainty_score":0.101738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008412804397240967,"score_gpt":0.2826013117225094,"score_spread":0.2741885073252684,"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."}}