Bibliographic record
Abstract
Review of European Studies 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. Review of European Studies 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 res@ccsenet.org. Reviewers for Volume 11, Number 4 Nikos Christofis, Shaanxi Normal University, Greece Eugenia Panitsides, University of Macedonia, Greece Florin Ionita, The Bucharest Academy of Economic Studies, Romania Tryfon Korontzis, Hellenic National School of Local Government, Greece Carmen Ramos, University of Oviedo, Spain Nunzia Di Cristo Bertali, Liverpool John Moores University, United Kingdom Gülce Başer, Boğaziçi University, Tukey Anna Cebotari, Academy of Economic Studies of Moldova, Republica Moldova Vicenta Gisbert, Universidad de La Laguna, Spain Sara Núñez Izquierdo, University of Salamanca, Spain Ioanna Efstathiou, University of the Aegean, Greece Muhammad Saud, Universitas Airlangga, Indonesia Gabriela Gruber, Lucian Blaga University of Sibiu, Romania Pinar Burcu Güner, Bielefeld University, Germany Carlos Teixeira, University of British Columbi, Canada Valeria Vannoni, University of Perugia, Italy Evangelos Bourelos, Institute of Innovation and Entrepreneurship, SWEDEN Natalija Vrecer, independent researcher, Slovenia Ani Derderian, WSU, USA Òscar Prieto-Flores, University of Girona, Spain Ludmila Ivancheva, Institute for the Study of Societies and Knowledge, Bulgarian Academy of Sciences, Bulgaria Emilia Salvanou, Hellenic Open University, Greece Aziollah Arbabisarjou, Zahedan University of Medical Sciences, Iran Arthur Becker-Weidman, Center For Family Development, USA Zining Yang, La Sierra University & Claremont Graduate University, USA Meenal Tula, University of Hyderabad, India Smita M. Patil, School of Gender and Development Studies, India Skaidrė Žičkienė, Šiauliai University, Lithuania Maria Pescaru, University of Pitești, ROMANIA Indrajit Goswami, N. L. Dalmia Institute of Management Studies and Research, India Patrick van Esch, Moravian College, Australia & US Ioan-Gheorghe Rotaru, ‘Timotheus’ Brethren Theological Institute of Bucharest, Romania Montserrat Crespi Vallbona, University of Barcelona, Spain
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 | 0.136 | 0.603 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.025 | 0.015 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.012 | 0.011 |
| Insufficient payload (model declined to judge) | 0.123 | 0.072 |
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".