Mapping International Co-authorship Networks in Border Studies (1986–2018)
Bibliographic record
Abstract
Border studies have become increasingly global over the past two decades. Yet, a network analysis of the articles published in the Journal of Borderlands Studies from 1986 to 2018 shows that less than half of them have one or more coauthors. Unlike in other scientific disciplines, where a growth of co-publications is observed, this proportion has not really changed over the last decade. Our paper also shows that major divisions can be found within border studies, which is no small paradox for a science supposedly cross-border by nature. Despite the overall global increase in scientific connectivity, internationally co-authored papers are still an exception in our field and scholars have a strong preference for publishing within their own country. Instead of a fully integrated community, they form a fragmented network whose main components are mainly located in the United States. Interviews with border experts reveal that various obstacles contribute to the current fragmentation of border studies. In addition to being separated by geographical distance and, sometimes, by actual walls, border scholars must also able to overcome the cognitive, social, organizational, and institutional distance that separate them.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.018 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".