{"id":"W3121907980","doi":"","title":"Framing Manipulations in Contests: A Natural Field Experiment","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"CONTEST; Framing (construction); Incentive; Economics; Productivity; Loss aversion; LOOM; Wage; Labour economics; Microeconomics; Demographic economics; Engineering; Political science; Economic growth","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00322308,0.00147116,0.000986518,0.0005186482,0.001379489,0.001144977,0.001299836,0.001890083,0.008218806],"category_scores_gemma":[0.00623602,0.0005603467,0.0006369833,0.0003753364,0.001846797,0.0007593271,0.001273992,0.002533788,0.000581229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009337492,"about_ca_system_score_gemma":0.001012215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001091303,"about_ca_topic_score_gemma":0.00182873,"domain_scores_codex":[0.9981855,0.0006765812,0.0001223678,0.0004054827,0.0003429072,0.0002672108],"domain_scores_gemma":[0.9917469,0.004491571,0.00133257,0.00106912,0.0003084917,0.001051372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.06742647,0.2713263,0.0373424,0.002677955,0.0008603983,0.00201282,0.009412687,0.0108742,0.4812208,0.03672799,0.008987313,0.07113076],"study_design_scores_gemma":[0.037144,0.3892245,0.2170771,0.0005663317,0.001669404,0.00116963,0.005511031,0.0801549,0.1454291,0.08361875,0.03753541,0.000899942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924691,0.00005112097,0.002384224,0.0001864589,0.0001034205,0.000908617,0.0001789722,0.00004273126,0.00367534],"genre_scores_gemma":[0.9815856,0.0001190276,0.009946655,0.000652348,0.0001042649,0.003490792,0.0002376655,0.00003029573,0.003833439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008218806,"threshold_uncertainty_score":0.02749461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1051158011715149,"score_gpt":0.4308856926460635,"score_spread":0.3257698914745486,"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."}}