At the Intersection of Disciplinary Practice and Science Policy: Publication Language Choices of Social Sciences and Humanities Scholars in Poland
Bibliographic record
Abstract
The choice of language for research publication is a strategic decision that balances such issues as efficient communication of results to the target audience, requirements of the grant agency, the guidelines of desirable publication venues, and promotion criteria. Previous studies have shown that social sciences and humanities (SSH) scholars tend to communicate research in at least two languages and that they increasingly publish in English in addition to national languages. Evidence for disciplinary differences in publication languages in the SSH comes primarily from bibliometric studies that span short evaluative periods. This study aims to provide a complementary perspective on the lifelong publication practices in the SSH in one national context, using data obtained in a survey carried out in Polish universities. Its main objective is to assess the degree of multilingualism of individual disciplines and academic seniority groups, establish which languages are used, and set the results in the context of country- and institution-level science policies. The results show that while all the disciplines are oriented toward internationalization, they have developed distinctive practices reflecting their engagement with locally relevant topics, involvement with projects on the regional or supranational level, and participation in global research. They also show that by prioritizing publication in top-tier international venues across the board, current science policies do not adequately consider disciplinary practices and target audiences.
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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 | 0.048 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.021 | 0.010 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".