{"id":"W4415263965","doi":"10.3390/economies13100298","title":"Female Wage Employment and Fertility in Kenya","year":2025,"lang":"en","type":"article","venue":"Economies","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Brock University; Bill and Melinda Gates Foundation","keywords":"Fertility; Wage; Context (archaeology); Socioeconomic status; Male female; Point (geometry); Total fertility rate; Hourly wage","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003260131,0.00004814254,0.00009828083,0.00008500971,0.0001442804,0.00006563703,0.00008823873,0.00003836976,0.0001642482],"category_scores_gemma":[0.00002432719,0.00004639858,0.00002131026,0.0001026762,0.0001642696,0.0001062024,0.00003877917,0.00004399823,0.000007912144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002433934,"about_ca_system_score_gemma":0.00004792058,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002535096,"about_ca_topic_score_gemma":0.07037418,"domain_scores_codex":[0.9995045,0.00005350109,0.0001129212,0.0001572349,0.0000303318,0.0001415308],"domain_scores_gemma":[0.9998026,0.00006295177,0.00001790395,0.00007875663,0.000006375489,0.00003134582],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000007008488,0.00002259802,0.8983629,0.000004983805,0.00001047401,5.429541e-7,0.009768538,0.000001294894,9.768384e-7,0.03996142,0.0004111496,0.05144814],"study_design_scores_gemma":[0.0001188098,0.000006522122,0.9215907,0.000008151595,0.000002373241,1.940915e-8,0.006478251,0.000004993533,0.00001660952,0.01976633,0.0519556,0.00005162718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.843347,0.000565544,0.000002542634,0.001725494,0.0001564938,0.00005777161,0.000002468245,0.0000198987,0.1541228],"genre_scores_gemma":[0.993728,0.0002009307,0.00004616711,0.0001212738,0.00001498641,0.00001212052,6.461689e-7,0.000001164208,0.005874726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.150381,"threshold_uncertainty_score":0.9465891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02938020713488691,"score_gpt":0.3103402003899808,"score_spread":0.2809599932550939,"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."}}