{"id":"W2921992914","doi":"10.1108/cms-10-2018-0703","title":"MNCs’ R&amp;D talent management in China: aligning practices with strategies","year":2019,"lang":"en","type":"article","venue":"Chinese Management Studies","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Multinational corporation; Originality; Talent management; Exploratory research; Context (archaeology); Business; Qualitative research; Subsidiary; Value (mathematics); China; Knowledge management; Marketing; Business administration; Process management; Sociology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006140382,0.0002488737,0.0002175502,0.002211707,0.00237048,0.002357905,0.0007768435,0.0003738569,0.00181223],"category_scores_gemma":[0.006066759,0.0001089142,0.0001645812,0.004076415,0.001599681,0.001182885,0.001571484,0.0003524213,0.0001320497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01131478,"about_ca_system_score_gemma":0.02395701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04879868,"about_ca_topic_score_gemma":0.06522875,"domain_scores_codex":[0.9972619,0.001123399,0.0002322771,0.0003106323,0.000559464,0.0005123391],"domain_scores_gemma":[0.9962096,0.001303367,0.0007075945,0.0002437518,0.0008641341,0.0006715785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001216562,0.0002836669,0.3919987,0.001815706,0.0000515727,0.001131397,0.1546891,0.00260539,0.005246157,0.02819396,0.004930257,0.4089324],"study_design_scores_gemma":[0.00002992912,0.0003389108,0.6705498,0.001096047,0.00007817823,0.0003637176,0.237365,0.004980363,0.003698495,0.005064556,0.07633705,0.00009801185],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9761332,0.001521617,0.002089358,0.004632057,0.0000318953,0.0001813476,0.00006978117,0.00002896488,0.01531176],"genre_scores_gemma":[0.9959326,0.0005452011,0.001541659,0.000190557,0.000004422777,0.0000637508,0.00002915847,0.00000240615,0.001690237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04879868,"threshold_uncertainty_score":0.09702927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.026575578195118,"score_gpt":0.2940462113363315,"score_spread":0.2674706331412134,"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."}}