{"id":"W4256392840","doi":"10.5465/ambpp.2015.13267abstract","title":"\"Human Resource Approaches to Retirement: Gatekeeping, Improvising, Orchestrating, and Partnering\"","year":2015,"lang":"en","type":"article","venue":"Academy of Management Proceedings","topic":"Human Resource and Talent Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Improvisation; Workforce; Gatekeeping; Demographics; Process (computing); Human resources; Resource (disambiguation); Business; Qualitative research; Adaptation (eye); Human resource management; Knowledge management; Public relations; Marketing; Sociology; Management; Psychology; Economics; Political science; Economic growth; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006121252,0.0002265233,0.0001835217,0.00095915,0.004308044,0.002148459,0.0009337541,0.0007370924,0.002160755],"category_scores_gemma":[0.009869622,0.0001749434,0.0001873001,0.0006393903,0.00575407,0.001880211,0.003414534,0.0009645058,0.000266346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002017075,"about_ca_system_score_gemma":0.0029803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003490665,"about_ca_topic_score_gemma":0.009055992,"domain_scores_codex":[0.9920013,0.006284339,0.0001649293,0.0002785141,0.0005016348,0.0007692442],"domain_scores_gemma":[0.993588,0.004022697,0.0007040209,0.0003373213,0.0004073857,0.0009406499],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005993246,0.00008555979,0.009563478,0.0001778087,0.000004898676,0.0006155287,0.9425304,0.0001416428,0.001440466,0.006781379,0.001857796,0.03674116],"study_design_scores_gemma":[0.000005077267,0.00006442156,0.006295511,0.000159978,0.000004767091,0.0003870454,0.9586682,0.0001643392,0.0007737007,0.0008464429,0.03261111,0.00001931968],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700099,0.0004856793,0.008905899,0.002976462,0.0000802236,0.0001290699,0.000052845,0.00004193348,0.01731797],"genre_scores_gemma":[0.9928495,0.0002448051,0.002024403,0.0005064072,0.00001045932,0.0000947153,0.00001666907,0.00001282694,0.004240269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006121252,"threshold_uncertainty_score":0.03237265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1740675179374512,"score_gpt":0.2720524163360566,"score_spread":0.09798489839860541,"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."}}