Smart Borders and Mobilities: Spaces, Zones, Enclosures
Bibliographic record
Abstract
The border has been called the fundamental political institution; and the bordering process is one of the most important roles for community, delineating between inside and outside, us and them, safe and dangerous, known and unknown.Borders represent both an appeal to the limits in politics and of political community, and a technology of limits -a means of defining what is possible in the governing of life itself.Yet, even as border management has taken on a renewed emphasis for policy makers, assessing the border's status as a definable, concrete entity or process has become increasingly problematic.As we write this editorial, for example, the British government announces the extension of biometric controls, security gates, scanning and screening into the public spaces of the railway station, shopping mall and sports stadium.In addition to its traditional geophysical characteristics, the border has taken on virtual, de-territorialized attributes as well.Castles, walled cities, and extensive border battlements have been replaced by gated communities, expansive border zones, and management by "remote control."The contemporary border is constituted as much by data-flows, artificial zones and spaces of enclosure that seep into the city and the neighbourhood, as by older state and geographic boundaries.This issue of Surveillance & Society considers the evolving character of the international border in the wake of new security and trade agreements, burgeoning state and commercial surveillance practices, and the increasing global mobility of persons, objects and information.Featured here are four full-length articles and a multi-media artistic presentation which draw attention to reconfigurations of the border catalyzed by the new security and surveillance regimes which have coalesced in the years following 9/11.The contributors explore a variety of theoretical and substantive issues including the historic origins of surveillance practices now associated with border regulation, the border's increasing dispersal into differentiated spatial and temporal zones, the emergence of new surveillance paradigms, the simulacral and performative aspects of border security, and the differential effects of border management and risk assessment for various categories of persons.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".