{"id":"W262929796","doi":"","title":"CRDCN Synthesis Series / Série Synthèses du RCCDR","year":2014,"lang":"fr","type":"article","venue":"Project Muse (Johns Hopkins University)","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workforce; Wage; Gender gap; Demographic economics; Economics; Labour economics; Gender pay gap; Sociology; Economic growth","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008322647,0.001169655,0.001477358,0.01291792,0.001647811,0.005828246,0.00188613,0.00114643,0.1565996],"category_scores_gemma":[0.03160116,0.0006110106,0.001220969,0.01878852,0.001455572,0.002805942,0.002647708,0.002213998,0.02890074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008963817,"about_ca_system_score_gemma":0.01233345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02423886,"about_ca_topic_score_gemma":0.02008759,"domain_scores_codex":[0.994443,0.002422109,0.0006425735,0.0005830216,0.001689559,0.0002197945],"domain_scores_gemma":[0.9820419,0.008125829,0.001154209,0.00218494,0.006159149,0.0003340268],"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":[0.0001655875,0.00005689003,0.0002943415,0.0211251,0.00009829883,0.00008167638,0.001374201,0.0005887459,0.0002132438,0.08661338,0.6791311,0.2102576],"study_design_scores_gemma":[0.00001065232,0.000008135367,0.0003826217,0.01056821,0.00002311963,0.00001940942,0.0003636326,0.00003033925,0.00009100191,0.001883663,0.9866124,0.00000673675],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001575985,0.3846047,0.0103383,0.02228868,0.05273293,0.002156494,0.03985484,0.0005983373,0.4858498],"genre_scores_gemma":[0.04052502,0.6352683,0.02651253,0.01111625,0.02227472,0.01046495,0.03834443,0.001331843,0.214162],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1565996,"threshold_uncertainty_score":0.523878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01804199997353704,"score_gpt":0.2190427641596731,"score_spread":0.201000764186136,"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."}}