Faces of globalization and the borders of states: from asylum seekers to citizens
Bibliographic record
Abstract
Intensifying processes of globalization have led to a series of tensions around the way in which even the most cosmopolitan democracies now treat people who move across their borders. Non-citizens have become problems. The postcolonial settler nation-states – Australia, Canada, the USA and others – were ‘founded’ by immigrants and refugees who moved globally to become citizens in these ‘new lands’. Such countries were made by migrants displacing indigenous others. However, in a conflict-ridden world in which the displacement of persons has become endemic – and in a media-connected world where the possibility of finding a better place to live has become increasingly imaginable and desired – these countries are now attempting to manage that global flow of people by stringent homeland security measures that are becoming increasingly problematic. While they are constituted through the modern imaginary of liberal democratic norms, human rights and rule of law, in each country over the last few years, rules have been bent, breached or bolstered in order to keep people out. The essay argues that given the globalization of people movement, the nation-state has reached the limits of responding though unilateral or even regional multilateral arrangements.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.040 |
| Scholarly communication | 0.016 | 0.014 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| 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".