{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002172264,0.0002822018,0.0005562527,0.0005076447,0.0003326071,0.0002385069,0.0007702494,0.0004488174,0.0001013503],"category_scores_gemma":[0.0007725941,0.0003474793,0.0001338576,0.0001466984,0.0004874616,0.0002113147,0.001428945,0.001693054,0.00001999411],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005322434,"about_ca_system_score_gemma":0.0009847777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01134772,"about_ca_topic_score_gemma":0.05514272,"domain_scores_codex":[0.9968772,0.0003932475,0.0007066519,0.0008165387,0.000297987,0.000908358],"domain_scores_gemma":[0.9983373,0.0005908949,0.0001687134,0.0005676688,0.0001260317,0.0002094367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005757507,0.002229947,0.4835906,0.0002429435,0.0003361577,0.0003801815,0.2446858,0.009495103,0.001436176,0.04500786,0.001922743,0.2100967],"study_design_scores_gemma":[0.008358496,0.0009780924,0.04773189,0.002949391,0.00005608653,0.00001411473,0.6846851,0.02095855,0.004520725,0.05573811,0.1669237,0.007085713],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7712893,0.001340442,3.652409e-7,0.001054445,0.001016046,0.001090815,0.00001546051,0.00004773186,0.2241453],"genre_scores_gemma":[0.9934323,0.003223036,0.0004902046,0.00009915608,0.0002540976,0.0005803079,0.00002696635,0.00003914235,0.001854811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4399993,"threshold_uncertainty_score":0.9998977,"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."}}