Reviewer Acknowledgements for International Business Research, Vol. 11, No. 1
Bibliographic record
Abstract
International Business Research wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated.International Business Research is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please find the application form and details at http://recruitment.ccsenet.org and e-mail the completed application form to ibr@ccsenet.org.Reviewers for Volume 11, Number 1 Alireza Athari, Eastern Mediterranean University, IranAnca Gabriela Turtureanu, “DANUBIUS” University Galati, RomaniaAshford C Chea, Benedict College, USAAurelija Burinskiene, Vilnius Gediminas Technical University, LithuaniaBenjamin James Inyang, University of Calabar, NigeriaCelina Maria Olszak, University of Economics in Katowice, PolandEva Mira Bolfíková, Univerzity of P. J. Šafárik in Košice, Slovak RepublicFevzi Esen, Istanbul Medeniyet University, TurkeyFilomena Izzo, University of Campania Luigi Vanvitelli, ItalyFlorin Ionita, The Bucharest Academy of Economic Studies, RomaniaFrancesco Ciampi, Florence University, ItalyGiuseppe Granata, University of Cassino and Southen Lazio, ItalyGuillaume Marceau, University of Aix-Marseille, FranceGuo Zi-Yi, Wells Fargo Bank, N.A., USAHanna Trojanowska, Warsaw University of Technology, PolandHeather Cooper Bisalski, Dalton State College, USAHuijian Dong, Pacific University, USAJanusz Wielki, University of Business in Wroclaw, PolandJolita Vveinhardt, Vytautas Magnus University, LithuaniaJorge Mongay-Hurtado, ESIC Business and Marketing School, SpainKaren Gulliver, Argosy University, Twin Cities, USAMaria J. Sanchez-Bueno, Universidad Carlos III se Madrid, SpainMaria-Madela Abrudan, University of ORADEA, RomaniaMithat Turhan, Mersin University, TurkeyMohamed Abdel Rahman Salih, Taibah University, Saudi ArabiaMuath Eleswed, American University of Kuwait, USAPascal Stiefenhofer, University of Brighton, UKRafael Hernandez Barros, Universidad Complutense de Madrid, SpainRaphaël Dornier, Université Savoie Mont Blanc, FranceRoberto Campos da Rocha Miranda, University Center Iesb, BrazilSerhii Kozlovskiy, Donetsk National University, UkraineShun Mun Helen Wong, The Hong Kong Polytechnic University, Hong KongSumathisri Bhoopalan, Sastra University, IndiaValeria Stefanelli, Università del Salento, ItalyWing-Keung Wong, Asia University, Taiwan, China
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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 | 0.005 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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 teacher head, 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".