Bibliographic record
Abstract
Citation (2016), "List of Contributors", Research in Personnel and Human Resources Management (Research in Personnel and Human Resources Management, Vol. 34), Emerald Group Publishing Limited, Bingley, pp. vii-viii. https://doi.org/10.1108/S0742-730120160000034004 Publisher: Emerald Group Publishing Limited Copyright © 2016 Emerald Group Publishing Limited P. Matthijs Bal School of Management, University of Bath, Bath, UK Ho Kwan Cheung Department of Psychology, George Mason University, Fairfax, VA, USA Gerald R. Ferris Department of Management, Florida State University, Tallahassee, FL, USA Paul G. W. Jansen Department of Management & Organization, VU University Amsterdam, Amsterdam, the Netherlands Molly Kilcullen Department of Psychology, George Mason University, Fairfax, VA, USA Eden King Department of Psychology, George Mason University, Fairfax, VA, USA Donald H. Kluemper Department of Managerial Studies, University of Illinois at Chicago, Chicago, IL, USA Alex Lindsey Department of Psychology, George Mason University, Fairfax, VA, USA Graham H. Lowman Department of Management, Culverhouse College of Commerce, University of Alabama, Tuscaloosa, AL, USA Louis D. Marino Department of Management, Culverhouse College of Commerce, University of Alabama, Tuscaloosa, AL, USA Hannah M. Markell Department of Psychology, George Mason University, Fairfax, VA, USA Charn P. McAllister Department of Management, Florida State University, Tallahassee, FL, USA Ashley Membere Department of Psychology, George Mason University, Fairfax, VA, USA Arjun Mitra Department of Managerial Studies, University of Illinois at Chicago, Chicago, IL, USA Eddy S. Ng Rowe School of Business, Dalhousie University, Halifax, NS, Canada Emma Parry Cranfield School of Management, Cranfield, Bedfordshire, UK Reginald L. Tucker Department of Management, Culverhouse College of Commerce, University of Alabama, Tuscaloosa, AL, USA Siting Wang Department of Managerial Studies, University of Illinois at Chicago, Chicago, IL, USA Book Chapters Research in Personnel and Human Resources Management Research in Personnel and Human Resources Management Research in Personnel and Human Resources Management Copyright Page List of Contributors Multigenerational Research in Human Resource Management Workplace Flexibility across the Lifespan Understanding and Reducing Workplace Discrimination Social Media use in HRM The Call of Duty: A Duty Development Model of Organizational Commitment Dark Triad Traits and the Entrepreneurial Process: A Person-Entrepreneurship Perspective About the Authors
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.729 | 0.744 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".