Bibliographic record
Abstract
Citation (2016), "List of Contributors", Global Talent Management and Staffing in MNEs (International Business and Management, Vol. 32), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S1876-066X20160000032015 Publisher: Emerald Group Publishing Limited Copyright © 2016 Emerald Group Publishing Limited Ramudu Bhanugopan School of Management and Marketing, Charles Sturt University, New South Wales, Australia Zoltan Buzady Central European University Business School, Budapest, Hungary Peter J. Dowling Department of Management and Marketing, La Trobe University, Victoria, Australia Joao Ferreira Management and Economics Department, University of Beira Interior, Covilhã, Portugal Ying Guo International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Jiangsu, China Charlotte Jonasson Aarhus University, Aarhus, Denmark Haiying Kang Australian Institute of Business, Adelaide, Australia Jakob Lauring Aarhus University, Aarhus, Denmark Yvonne McNulty RMIT University, Sentosa Cove, Singapore Snejina Michailova University of Auckland Business School, Auckland, New Zealand Yoko Naito School of Political Science and Economics, Department of Business Administration, Tokai University, Kanagawa, Japan Dana L. Ott University of Auckland Business School, Auckland, New Zealand Hussain G. Rammal UTS Business School, University of Technology Sydney, NSW, Australia Vanessa Ratten La Trobe Business School, La Trobe University, Victoria, Australia Jan Selmer Aarhus University, Taby, Sweden Jie Shen Shenzhen International Business School, Shenzhen University, Guangdong, People’s Republic of China Justin Williams School of Business and Management, Niagara College, Niagara on the Lake Ontario, Canada Ling Eleanor Zhang King’s College London, School of Management & Business, London, United Kingdom Book Chapters Global Talent Management and Staffing in MNEs International Business & Management Global Talent Management and Staffing in MNEs Copyright Page List of Contributors About the Editors About the Authors Global Talent Management and Staffing in MNEs: An Introduction to the Edited Volume of International Business and Management Acknowledgements Expatriate Selection: A Historical Overview and Criteria for Decision-Making Global Talent Management: International Staffing Policies and Practices of South Korean Multinationals in China How do Assigned and Self-Initiated Expatriate CEOs Differ? An Empirical Investigation on CEO Demography, Personality, and Performance in China Career Capital Development of Self-Initiated Expatriates in China Multiple Aspects of Readjustment Experienced by International Repatriates in Multinational Enterprises: A Perspective of ‘Changes Occurring Over Time’ and ‘Changes due to Cultural Differences’ Why Expatriate Compensation Will Change How We Think about Global Talent Management Global Talent Management and Corporate Entrepreneurship Strategy The Effects of Work Values and Organisational Commitment on Localisation of Human Resources Talent Management & Staffing in Central and Eastern Europe — An Analysis of Bulgaria, Czech Republic, Hungary, Poland, Romania & Slovakia
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.110 | 0.007 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".