Reviewer Acknowledgements for International Business Research, Vol. 10, No. 8
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 10, Number 8 Alireza Athari, Eastern Mediterranean University, IranAnca Gabriela Turtureanu, “DANUBIUS” University Galati, RomaniaAnna Paola Micheli, Univrtsity of Cassino and Southern Lazio, ItalyArash Riasi, University of Delaware, USAAurelija Burinskiene, Vilnius Gediminas Technical University, LithuaniaBenjamin James Inyang, University of Calabar, NigeriaBrian Sheehan, Thaksin University, ThailandBruno Marsigalia, University of Casino and Southern Lazio, ItalyCelina Maria Olszak, University of Economics in Katowice, PolandFevzi Esen, Istanbul Medeniyet University, TurkeyFrancesco Ciampi, Florence University, ItalyGeorgeta Dragomir, “Danubius” University of Galati, RomaniaGianluca Ginesti, University of Naples “FEDERICO II”, ItalyGilberto Marquez-Illescas , Clarkson University , USAGuillaume Marceau, University of Aix-Marseille, FranceHanna Trojanowska, Warsaw University of Technology, PolandHerald Monis, Milagres College, IndiaHung-Che Wu, Nanfang College of Sun Yat-sen University, ChinaIonela-Corina Chersan, “Alexandru Ioan Cuza” University from Iași, RomaniaIvo De Loo, Nyenrode Business University, The NetherlandsKaren Gulliver, Argosy University, Twin Cities, USAL. Leo Franklin, Bharathidasn University, IndiaLadislav Mura, University of Ss. Cyril and Methodius in Trnava, SlovakiaManlio Del Giudice, University of Rome "Link Campus", ItalyManuela Rozalia Gabor, “Petru Maior” University of Tîrgu Mureş, RomaniaMaria João Guedes, University of Lisbon, PortugalMaria Teresa Bianchi, University of Rome “LA SAPIENZA”, ItalyMaria-Madela Abrudan, University of ORADEA, RomaniaMiriam Jankalová, University of Zilina, SlovakiaMiroslav Iordanov Mateev, American University, Dubai, UAEMithat Turhan, Mersin University, TurkeyMohamed Abdel Rahman Salih, Taibah University, Saudi ArabiaMohamed Rochdi Keffala, University of Kairouan, TunisiaMuath Eleswed, American University of Kuwait, USAOnur Köprülü, Mersin University, TurkeyOzgur Demirtas, Turkish Air Force Academy, TurkeyPascal Stiefenhofer, University of Brighton, UKRafiuddin Ahmed, James Cook University, AustraliaRoberto Campos da Rocha Miranda, University Center Iesb, BrazilRosa Lombardi, Sapienza University of Rome, ItalyRoxanne Helm Stevens, Azusa Pacific University, USASerhii Kozlovskiy, Donetsk National University, UkraineTariq Tawfeeq Yousif Alabdullah, University of Basrah, IraqValeria Stefanelli, Università del Salento, ItalyWejdene Yangui, Institute of High Business Studies of Sfax _ Tunisia (IHEC), TunisiaWing-Keung Wong, Asia University, Taiwan, ChinaYan Lu, University of Central Florida, USA
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 | 0.013 | 0.353 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.014 |
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".