Media representation of African individuals in Australia during the COVID-19 pandemic and its impact on mental health
Bibliographic record
Abstract
Abstract The COVID-19 crisis has profoundly impacted mental health globally, including in Australia. This study focuses on the media representation of Australians of African descent during the pandemic and its unintended effects on mental health. Media coverage of COVID-19 restriction breaches by individuals from African backgrounds in Australia has contributed to significant emotional and mental distress. Through content analysis of media content from popular Australian publications, we examined the prevalence of racially motivated rhetoric surrounding COVID-19 breaches within culturally and linguistically diverse communities. Our findings consistently emphasise the term "Covidiots" when reporting on COVID-19 breaches among individuals from African backgrounds. Specifically, three African girls were subjected to ongoing harassment, public shaming, and criminalization by the Australian media in relation to COVID-19 breaches, in comparison to other racial groups. These findings underscore the consistent portrayal of people from African communities as outsiders and the racial profiling they experience in media coverage of significant issues like COVID-19. Such portrayals have the potential to negatively impact mental health.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".