{"id":"W3174527793","doi":"","title":"Deploying ‘Connectors’: A Control to Manage Employee Turnover Intentions?","year":2019,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Customer Service Quality and Loyalty","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Turnover; Control (management); Affect (linguistics); Work (physics); Psychology; Turnover intention; Social psychology; Test (biology); Business; Engineering; Job satisfaction; Communication; Management; Economics; Biology; Ecology","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":[0.002106056,0.0003514549,0.0002113918,0.0005352162,0.001346827,0.002068118,0.000587978,0.0007144221,0.004494593],"category_scores_gemma":[0.007993744,0.0001862499,0.0001882729,0.0004044296,0.001770547,0.00130544,0.001953724,0.0007306255,0.0005081493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005436373,"about_ca_system_score_gemma":0.001108505,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234357,"about_ca_topic_score_gemma":0.003185426,"domain_scores_codex":[0.9984428,0.0007392829,0.00005327201,0.0002535029,0.000236308,0.0002747592],"domain_scores_gemma":[0.9908991,0.001601155,0.002476572,0.001119136,0.0004644396,0.003439509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009930537,0.004889392,0.5499279,0.0002610882,0.0002075439,0.0008268753,0.02561877,0.001363959,0.05456968,0.02682058,0.004997904,0.3295232],"study_design_scores_gemma":[0.0002258732,0.004145856,0.8998199,0.0001816544,0.0002177758,0.0008305711,0.03671067,0.008996001,0.006339802,0.01617127,0.02623971,0.000120872],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861228,0.00005906236,0.004896353,0.000797821,0.00003401195,0.00005065495,0.00001101388,0.00006547465,0.00796286],"genre_scores_gemma":[0.9973198,0.00002651667,0.001773107,0.000129452,0.00001892895,0.00002383708,0.00001321347,0.000006119649,0.0006891061],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004494593,"threshold_uncertainty_score":0.01503599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01093874529037354,"score_gpt":0.2327654018802388,"score_spread":0.2218266565898653,"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."}}