Borderscapes Inside Out: New Transdisciplinary Methodological Horizons for Critical Border Studies
Bibliographic record
Abstract
In critical border studies, interdisciplinary approaches are often stressed as pivotal analytical perspectives for obtaining a comprehensive understanding of borderscaping dynamics. However, the substantial contributions in this direction made by social sciences, humanities, and border studies are often limited to a theoretical and conceptual layer. The increasingly mobile, de/re/territorialized, and processual dimensions of contemporary borders require an additional step. We are still lacking adequate transdisciplinary methodological instruments to operationalize our theoretical knowledge of the complexity of b/ordering processes. What functional tactics could be used to address this necessity? This article suggests that (re)conceiving the border not only as a subject but also as a transdisciplinary method is the epistemic frame through which to answer this question. Specifically, we discuss the design of our participatory action-research within the BorderArt(E)Scapes project as a tool for developing new applied transdisciplinary research methodologies that enhance the dialogue between anthropological, artistic, art-historical, and educational perspectives.
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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 | 0.098 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.016 | 0.096 |
| Scholarly communication | 0.037 | 0.049 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".