{"id":"W4409731306","doi":"10.1108/ccij-10-2024-0188","title":"Decoding the Pygmalion language of top CEOs: the communication of high positive expectations in CEO letters","year":2025,"lang":"en","type":"article","venue":"Corporate Communications An International Journal","topic":"Management and Organizational Studies","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Douglas College","funders":"","keywords":"Business; Decoding methods; Psychology; Public relations; Telecommunications; Political science; Computer 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":[],"consensus_categories":[],"category_scores_codex":[0.0005589866,0.00008933007,0.0001210242,0.0004070822,0.0004520279,0.0001980575,0.001965886,0.00001928335,0.00006290898],"category_scores_gemma":[0.0002021387,0.00006325601,0.00005379891,0.0007771704,0.0002465195,0.0007108151,0.0006408553,0.0001992027,0.000005358449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005843716,"about_ca_system_score_gemma":0.00002986121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008002092,"about_ca_topic_score_gemma":0.001250026,"domain_scores_codex":[0.9990169,0.0001023689,0.00047165,0.00008448601,0.0002395551,0.00008500909],"domain_scores_gemma":[0.9976501,0.0002629198,0.0007840042,0.000597841,0.0007001575,0.000004904758],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00005885962,0.0003131432,0.1387589,0.00002013321,0.0002522761,0.000002062094,0.003289058,0.001085747,0.001382056,0.8437434,0.002236759,0.008857672],"study_design_scores_gemma":[0.001452018,0.00001957091,0.8743241,0.0005469114,0.000190892,0.000007552263,0.03685713,0.01014844,0.0008462061,0.07217145,0.003147317,0.0002884621],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9563298,0.001112266,0.003918461,0.03098687,0.0003531403,0.0002950986,0.00001287767,0.00002127237,0.006970263],"genre_scores_gemma":[0.9971033,0.0004826889,0.001246829,0.0008170995,0.00009341409,0.00001630883,0.0001209964,0.000007908227,0.000111402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7715719,"threshold_uncertainty_score":0.3653139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02770600920775316,"score_gpt":0.2809185048152438,"score_spread":0.2532124956074907,"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."}}