{"id":"W3175416013","doi":"10.1111/tesg.12488","title":"Gender, Space, and Precarious Employment in Canada","year":2021,"lang":"en","type":"article","venue":"Tijdschrift voor Economische en Sociale Geografie","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Census; Metropolitan area; Geography; Demographic economics; American Community Survey; Survey data collection; Economic geography; Sociology; Economics; Demography; Population","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005414424,0.0002017642,0.0004059784,0.0000670022,0.0005803333,0.0001301514,0.0001792542,0.0001530565,0.0006707462],"category_scores_gemma":[0.0002727574,0.0002360232,0.00008049855,0.0002636182,0.0001885539,0.0002102433,0.0001318006,0.00024723,0.00003489575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004713052,"about_ca_system_score_gemma":0.004696822,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8819572,"about_ca_topic_score_gemma":0.9931406,"domain_scores_codex":[0.9980386,0.0002942508,0.0003702627,0.0004522489,0.0002569795,0.0005876319],"domain_scores_gemma":[0.9989355,0.000419972,0.0001241155,0.0001940489,0.0001125944,0.0002138114],"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":[0.00002465875,0.0001224354,0.8498974,0.00003710208,0.0002963115,0.00009355335,0.04363425,0.00004225438,0.00003273648,0.06593429,0.02050582,0.01937922],"study_design_scores_gemma":[0.00121704,0.0000156032,0.1769597,0.0000161291,0.00004438086,0.000002350475,0.02780962,0.00004251524,0.0001076216,0.001763343,0.7915431,0.0004785615],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7674814,0.005778202,0.0000195482,0.005657553,0.000808866,0.000378685,0.00004512602,0.00007245185,0.2197581],"genre_scores_gemma":[0.9892025,0.001630726,0.0002250695,0.0006202987,0.0004411069,0.00005530901,0.00001507093,0.00002152237,0.007788391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7710373,"threshold_uncertainty_score":0.9624745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02033318117051785,"score_gpt":0.2528809815726115,"score_spread":0.2325478004020937,"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."}}