{"id":"W3140608428","doi":"10.1086/735032","title":"The Role of Nonemployers in Business Dynamism and Aggregate Productivity","year":2025,"lang":"en","type":"article","venue":"Journal of Political Economy Macroeconomics","topic":"Firm Innovation and Growth","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Dynamism; Productivity; Context (archaeology); Slowdown; Aggregate (composite); Quarter (Canadian coin); Economics; Business cycle; Total factor productivity; Industrial organization; Labour economics; Business; Macroeconomics; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001356489,0.0001684837,0.0003415914,0.001501647,0.0003760703,0.001672864,0.0004033045,0.0005749147,0.002427764],"category_scores_gemma":[0.007801067,0.0001502287,0.0004076819,0.001641536,0.0009115453,0.001814709,0.001135404,0.0008847935,0.0003912234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001187691,"about_ca_system_score_gemma":0.0006524023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005029277,"about_ca_topic_score_gemma":0.005965204,"domain_scores_codex":[0.9996117,0.00007170808,0.00002564043,0.00008527744,0.00006775169,0.0001379322],"domain_scores_gemma":[0.984511,0.005951598,0.006700761,0.0006202186,0.0006867192,0.001529778],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000227214,0.0001221802,0.9403603,0.00007806252,0.0000938477,0.0005805955,0.0006528398,0.01706636,0.002043782,0.01555958,0.001179646,0.0220356],"study_design_scores_gemma":[0.00002127216,0.0001057914,0.9394632,0.00004416215,0.00004869846,0.0003195509,0.0008894263,0.03418499,0.001434137,0.01923486,0.004223685,0.00003019532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913406,0.000699147,0.002165262,0.0008789161,0.00001107969,0.000009201102,0.0005382845,0.00002314344,0.004334368],"genre_scores_gemma":[0.9988784,0.0002038131,0.0001376825,0.00002042415,0.00001875389,0.000002851007,0.0001322957,0.000001906035,0.0006039287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005029277,"threshold_uncertainty_score":0.01000005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006916736939096157,"score_gpt":0.2151830530355002,"score_spread":0.2082663160964041,"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."}}