{"id":"W4413604981","doi":"10.64628/aam.nedcacd64","title":"Canada’s digital nomad program could attract tech talent – but would they settle down?","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Virginia tech; Business; High tech; Management; Political science; Economics; Library science; Law; Computer science","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":[0.004643073,0.0005651563,0.0006499001,0.002062498,0.0106815,0.01490921,0.001748305,0.008024013,0.07916469],"category_scores_gemma":[0.01332661,0.000357847,0.0006869612,0.002381768,0.003176762,0.00619787,0.002669001,0.005500143,0.0074289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04291145,"about_ca_system_score_gemma":0.1651758,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9488682,"about_ca_topic_score_gemma":0.9764181,"domain_scores_codex":[0.9938956,0.0002806767,0.00006554566,0.0002542786,0.002600256,0.002903634],"domain_scores_gemma":[0.9862586,0.0009421253,0.0002337389,0.0002649555,0.006583778,0.005716808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001370928,0.0001062669,0.006055234,0.00009255695,0.00003572788,0.0001331524,0.0004522148,0.0001589857,0.0002705126,0.1194478,0.8275527,0.04555771],"study_design_scores_gemma":[0.0001086866,0.00006328852,0.01613215,0.0003301314,0.00004771977,0.00005182412,0.00434945,0.0008449615,0.0008222869,0.01738454,0.9597502,0.0001148231],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.01821529,0.002722918,0.001088456,0.695926,0.004443656,0.0001689096,0.002961105,0.0003838535,0.2740898],"genre_scores_gemma":[0.231205,0.003091614,0.004068298,0.1321812,0.001031769,0.0001430691,0.001360961,0.0002835338,0.6266347],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07916469,"threshold_uncertainty_score":0.3113458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03692965464750094,"score_gpt":0.2479318097548175,"score_spread":0.2110021551073166,"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."}}