{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006185042,0.0001447722,0.0004988515,0.0006186392,0.0002739936,0.0000743382,0.0007676679,0.0003884264,0.0002012451],"category_scores_gemma":[0.003261717,0.0001613266,0.00006453715,0.0002076307,0.0003241592,0.0002460879,0.0005818525,0.0006610233,0.00002867293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002718635,"about_ca_system_score_gemma":0.005096019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.0233838,"about_ca_topic_score_gemma":0.05357673,"domain_scores_codex":[0.9976611,0.0001550586,0.0006324539,0.000633413,0.0005848645,0.0003330811],"domain_scores_gemma":[0.9975489,0.001426646,0.0002158742,0.0002539908,0.0004216375,0.0001329834],"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":[0.00004858986,0.00006199993,0.04718451,0.0001684754,0.0002405784,0.000004628419,0.003120006,0.000008901256,6.644614e-7,0.1925318,0.7476409,0.008988924],"study_design_scores_gemma":[0.0002011353,0.00003074936,0.002997437,0.00003803171,0.000006132076,9.682362e-7,0.0009366937,0.0000236596,0.000001550294,0.08626132,0.9093198,0.000182502],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001530244,0.00225233,0.000001049245,0.01402935,0.0006140521,0.0003772567,0.00008271488,0.00001279101,0.9811002],"genre_scores_gemma":[0.7479872,0.2268845,0.0006707655,0.0003091759,0.004402966,0.0001475393,0.0008716665,0.00005645316,0.01866971],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9624305,"threshold_uncertainty_score":0.9831195,"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."}}