{"id":"W3092303448","doi":"10.3386/w27918","title":"Ethnographic and Field Data in Historical Economics","year":2020,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Culture, Economy, and Development Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Ethnography; Field (mathematics); Sociology; Data science; Computer science; Anthropology; Mathematics","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":[0.02592427,0.0006812259,0.0008454947,0.01451672,0.003485264,0.005087451,0.001542697,0.001803562,0.02933621],"category_scores_gemma":[0.07658543,0.0008007037,0.0004182521,0.02707611,0.006115134,0.01032008,0.004784198,0.002270709,0.002984972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003965282,"about_ca_system_score_gemma":0.004332384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01293569,"about_ca_topic_score_gemma":0.01637124,"domain_scores_codex":[0.9636078,0.02858217,0.001947281,0.00169172,0.003526232,0.0006448068],"domain_scores_gemma":[0.8626422,0.1055523,0.009953951,0.01320912,0.007198296,0.001444074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001197661,0.0001978912,0.02705216,0.002286423,0.00007449907,0.0003447602,0.01975314,0.001384449,0.0002086885,0.6672007,0.06731917,0.2140583],"study_design_scores_gemma":[0.00005110451,0.0001152878,0.03453105,0.00591644,0.00004755853,0.0004580154,0.02687044,0.0008965945,0.0004780538,0.200471,0.7300683,0.00009601838],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05571431,0.04975223,0.1402379,0.02561762,0.003210128,0.004133426,0.0293702,0.0003028503,0.6916614],"genre_scores_gemma":[0.5361387,0.08502266,0.2533458,0.01162664,0.004238884,0.01991059,0.02672646,0.0004330373,0.0625573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02933621,"threshold_uncertainty_score":0.1371022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.68136111455992,"score_gpt":0.5702031976274717,"score_spread":0.1111579169324483,"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."}}