{"id":"W7114919646","doi":"10.2139/ssrn.5847362","title":"Screening Precommitment, Candidate Quality, and Time-to-Hire: An Experimental Investigation","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; McMaster University","funders":"","keywords":"Precommitment; Satisficing; Earnings; Quality (philosophy); Control (management)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03319805,0.00112631,0.002408914,0.0009632926,0.00201887,0.004373109,0.003490463,0.004150643,0.0272557],"category_scores_gemma":[0.1472865,0.001217508,0.001289069,0.001154565,0.003512172,0.003941144,0.002757081,0.004167337,0.002231871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001302716,"about_ca_system_score_gemma":0.003334257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002438877,"about_ca_topic_score_gemma":0.002647444,"domain_scores_codex":[0.9876952,0.007604188,0.0007628819,0.001796237,0.001180345,0.0009612003],"domain_scores_gemma":[0.5140972,0.4265798,0.02671198,0.02332317,0.002599538,0.006688383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"randomized_trial","study_design_scores_codex":[0.3236811,0.2220787,0.2965499,0.001502823,0.002480147,0.0010314,0.005927103,0.01068524,0.02207658,0.02155842,0.004177169,0.08825142],"study_design_scores_gemma":[0.06113835,0.3068985,0.4387512,0.0003391934,0.005532126,0.001171853,0.006308046,0.08569217,0.01467513,0.07133453,0.007344321,0.000814678],"study_design_candidate":"randomized_trial","study_design_consensus":"randomized_trial","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945639,0.0002174443,0.001949167,0.0003251118,0.00005237455,0.0004706298,0.000252624,0.00003204448,0.002136623],"genre_scores_gemma":[0.9908978,0.0001188021,0.00244311,0.000250491,0.00008617611,0.0007283796,0.000272121,0.00002123072,0.005181879],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03319805,"threshold_uncertainty_score":0.1755701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05727614806434175,"score_gpt":0.3874864087830882,"score_spread":0.3302102607187464,"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."}}