Fear and Loathing Down Under: Australian Refugee Policy and the National Imagination
Bibliographic record
Abstract
This paper looks at Australia’s refugee policy in light of incidents that took place in the summer of 2001, with the refugees aboard the Tampa. Analyzing the discourse that resulted from these incidents, I show how Australia believes it is a nation under threat that prides itself as generously welcoming as many refugees as it can and who, of late, is only trying to protect its borders from so-called refugees who really are “queue jumpers.” I contrast this view with what emerges from the facts: that Australia’s racialized past makes it very easy for it to believe that it is under siege from refugees, and that it has done all that is legally possible to disinvest itself from its international obligations. This has meant turning boats away at sea, excising certain territories from its jurisdiction, and interning the refugees who arrive in Australia. Through this analysis, I argue that the current policy is a re-emergence of the earlier White Australia policy.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.035 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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".