Rethinking Borders Through a Complexity Lens: Complex Textures Towards a Politics of Hope
Bibliographic record
Abstract
This article aims to explore the potential of a complexity approach for promoting a more comprehensive understanding of b/ordering processes and their relation to contemporary post-global phenomena. Specifically, the paper - which is theoretical rather than empirical - sets out two aims. On the one hand, to show how a complexity approach - with a focus on Morin’s “complex thought” - is helpful for advancing research on borders, thereby establishing a dialogue with the conceptualization of borderscapes and bordertextures within critical border studies. On the other hand, to reflect on how theoretical knowledge on border complexities can be operationalized through anthropological reflections on cultural complexity and borders. The article concludes by considering how borders as complex textures might be reinterpreted as a space of political creativity, where it may also be possible to cultivate a politics of hope, thereby opening up the way to alternative political subjectivities and agencies.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.078 |
| Scholarly communication | 0.022 | 0.019 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".