Differentiation, Affected Temporalities and the Politics of Inclusion and Exclusion of the Border Regime
Bibliographic record
Abstract
This article addresses the question of how differentiation functions as a fundamental criterion for the global border regime. Drawing on qualitative fieldwork in Finland and Mexico, we show how differentiation is instrumentalized by states and enables a complicated process of inclusion and exclusion that in some cases continues even after migration ends. We argue that differentiation is a precondition of the border regime, influencing the entire temporal experience of migration and its consequences and creating a persistent hierarchization of different social groups. As such, it sustains a variety of practices of border control and has a direct impact on the experiences and temporalities in the context of human mobility. In the analysis, attention is paid to how criteria such as racialization and country of origin are enforced and impact temporalities. In the case of our participants, differentiation relates to personal and social uncertainty at different stages and a contradictory sense of belonging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".