{"id":"W4389188885","doi":"10.2139/ssrn.4635599","title":"The signals we give: Performance feedback, gender, and competition","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Negative feedback; Competition (biology); Valence (chemistry); Gender bias; SPARK (programming language); Psychology; Representation (politics); Positive feedback; Social psychology; Cognitive psychology; Computer science; Political science","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.001871338,0.00007856658,0.00009010141,0.00004279653,0.00233956,0.0001365463,0.0001828797,0.00003620496,0.00001859683],"category_scores_gemma":[0.00002145434,0.00006106142,0.00004178642,0.0001504447,0.0002660518,0.0002104212,0.00005535834,0.0005069326,0.0001035236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005902637,"about_ca_system_score_gemma":0.0004956293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001188687,"about_ca_topic_score_gemma":0.001616958,"domain_scores_codex":[0.9981917,0.00009336828,0.0001506645,0.0001106706,0.0001712462,0.001282331],"domain_scores_gemma":[0.999679,0.00008315918,0.00008348103,0.00005840382,0.00003812018,0.00005783683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003364679,0.00002495383,0.01166352,0.000004097905,0.00008884999,0.000001876047,0.009895858,0.00001895302,0.001205622,0.9378549,0.0005716329,0.03863601],"study_design_scores_gemma":[0.0009592843,0.0004332283,0.01436261,0.00003935183,0.00004584638,0.00007775513,0.3216548,0.0001561206,0.0006371625,0.6058421,0.05532007,0.0004717164],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978317,0.007492392,0.00001737573,0.004126985,0.000278857,0.0001206021,0.00000128854,0.00005222815,0.009593247],"genre_scores_gemma":[0.8585746,0.1390212,0.000006569453,0.00003202322,0.0001799836,0.000007820357,7.509675e-7,0.000007690519,0.002169396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3320129,"threshold_uncertainty_score":0.9989592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0309511899302453,"score_gpt":0.312203027140082,"score_spread":0.2812518372098367,"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."}}