Bibliographic record
Abstract
Abstract This article examines public information campaigns designed to deter asylum seekers from entering Australia via boat. Through analysing the institutional context and content of a graphic novel that was circulated within Afghan Hazara communities in 2014, I show that certain Australian public information campaigns mobilize an ethos of cultural sensitivity rooted in ethnographic data-gathering projects that reinscribe migrants as ignorant and socially deviant subjects. Such campaigns both situate Australia as an impossible destination and render migration a dangerous, futile act that will bring further misfortune to migrants’ families. The Australian case shows that in contexts where cultural sensitivity and externalized border control simultaneously guide migration policy, cultural knowledge becomes weaponized not only to keep migrants immobile but also to discipline migrant subjectivity and ultimately exclude them from pathways to refuge.
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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 | 0.015 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.024 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".