{"id":"W4405059575","doi":"10.2139/ssrn.4988437","title":"Home Production and Gender Gap in Structural Change","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Production (economics); Structural change; Economic geography; Business; Economics; Market economy; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001493942,0.0001480746,0.0003810757,0.001240171,0.001076959,0.001733866,0.0004600372,0.000843565,0.02104177],"category_scores_gemma":[0.006188936,0.0001007014,0.0001887494,0.001707785,0.002651134,0.001999503,0.001901489,0.0007128878,0.0004326913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001235081,"about_ca_system_score_gemma":0.001059836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005997089,"about_ca_topic_score_gemma":0.007519786,"domain_scores_codex":[0.9991249,0.0003426566,0.00002051083,0.0001253874,0.0000731121,0.0003133964],"domain_scores_gemma":[0.9959596,0.002695781,0.0004804339,0.0001226461,0.0001348538,0.0006065908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001379333,0.0008912671,0.4850834,0.0002605869,0.0001193343,0.0009411574,0.04378508,0.002779851,0.0009196186,0.3956829,0.005074039,0.06308334],"study_design_scores_gemma":[0.0001008382,0.0003147683,0.6997001,0.0002173368,0.00004831414,0.000232923,0.09885838,0.00361058,0.0006255314,0.1832835,0.012984,0.0000238279],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9708099,0.001151766,0.0006968266,0.003844187,0.00004473727,0.000009370031,0.0002702649,0.000007858239,0.02316513],"genre_scores_gemma":[0.9989389,0.0001384584,0.00002919068,0.00003067957,0.00001606715,0.000004102309,0.00002589033,0.000002128118,0.0008145732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02104177,"threshold_uncertainty_score":0.07039177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03630122079244308,"score_gpt":0.3048869470726419,"score_spread":0.2685857262801988,"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."}}