Internationalization of Polish Journals in the Social Sciences and Humanities: Transformative Role of The Research Evaluation System
Bibliographic record
Abstract
This article discusses the transformations of Polish journals caused by the Polish Journal Ranking evaluation system. We focused on the internationalization of journals in the social sciences and humanities (N = 801), with the goal of investigating how science policy has transformed editorial practices at Polish journals. We used a mixed-method approach involving both one-way analysis of variance, two-way mixed design analysis of variance, and semi-structured interviews. Our findings showed that science policy has transformed editorial practices, but that there is no actual internationalization in Polish social sciences and humanities journals. Rather, there is only the ostensible internationalization that manifests in “gaming” the journal evaluation system. We found that the editors of Polish journals do not discuss the challenges of internationalization, and implement only those internationalization practices that are explicitly required in the system regulations. We conclude with recommendations for how to motivate the internationalization of journals and stem the corruption of parameters measuring internationalization.
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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 | 0.147 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".