{"id":"W1493129960","doi":"10.3386/w23128","title":"Land Misallocation and Productivity","year":2017,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Land Rights and Reforms","field":"Agricultural and Biological Sciences","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Ministerio de Economía y Competitividad","keywords":"Total factor productivity; Productivity; Agriculture; Panel data; Agricultural productivity; Capital (architecture); Inequality","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":[0.002437541,0.00009218335,0.0002135908,0.00004045808,0.0003028412,0.00008020797,0.0002450458,0.0002216988,0.0001135076],"category_scores_gemma":[0.000274648,0.00001968176,0.00005440266,0.00003125764,0.0002220978,0.0001153178,0.00009952667,0.0002472226,0.0000281948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000176484,"about_ca_system_score_gemma":0.0004332631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005594811,"about_ca_topic_score_gemma":0.002983829,"domain_scores_codex":[0.9986647,0.00004574851,0.0002006957,0.0003100137,0.0006119463,0.0001668592],"domain_scores_gemma":[0.9987757,0.0001988052,0.000181808,0.0000701143,0.0007157185,0.00005784703],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001935563,0.0004627114,0.05533539,0.0006096708,0.0004386897,0.00000807826,0.0001185995,0.00002030699,0.007852833,0.02447783,0.1692006,0.7412817],"study_design_scores_gemma":[0.0001345368,0.0001494426,0.1133675,0.00008058191,0.000007111062,0.00002443283,0.000009935389,0.00003419161,0.0003888572,0.1298026,0.7558215,0.0001792504],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2658244,0.001015887,8.021401e-8,0.009154365,0.0008430119,0.0008290157,0.0002624349,0.00002106674,0.7220497],"genre_scores_gemma":[0.9312201,0.002812554,0.000009339112,0.000003211185,0.002299079,0.00002051679,0.0005341459,0.000001381452,0.06309965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7411025,"threshold_uncertainty_score":0.8457718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.332625290160024,"score_gpt":0.464080553166523,"score_spread":0.131455263006499,"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."}}