Refugees and asylum seekers in Australian print media: A critical discourse analysis
Bibliographic record
Abstract
The occupational possibilities available to refugees and asylum seekers upon arrival in Australia are influenced by the discourses in Australian print media that shape knowledge, attitudes, and subjectivities, including which people and what occupations are ideal and possible. This paper sought to expose and challenge discourses constructing subjectivities and shaping the occupational possibilities or occupational injustices for refugees and asylum seekers within the Australian context. A critical discourse analysis of Australian local and national newspapers was conducted. A theoretical framework constructed from the work of Foucault and Fairclough was applied, with findings informed by an occupational science perspective. Three core subjectivities were identified in the print media discourse: wretched identities, suspicious fugitives, and cultural usurpers. These constructions highlighted the way in which discourses within the Australian print media can limit occupational possibilities for refugees and asylum seekers to those occupations relevant only to survival, surveillance, or assimilation. Implications for occupational possibilities may include occupationally restrictive boundaries upon resettlement and justification for excluding refugees and asylum seekers from Australian society. The disempowering nature of these subjectivities reflects aspects of Australian discourses that should be and can be challenged.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.015 | 0.022 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".