International images and mass media: the effects of media coverage on Canadians' perceptions of ethnic and race relations in Australia
Bibliographic record
Abstract
Recently, there has been much speculation about the impact of international media coverage of Australia's position on Indigenous people, migrants and asylum seekers on other nations' images of Australia. In this experiment we examined whether there was any basis for such concerns by considering the short-term impact of negative TV coverage of Australians on Canadian viewers. A questionnaire provided baseline data on Canadian students' perceptions of Australians and Australian race relations. Four months later, the students were assigned to one of three conditions that varied media contact with Australians. Students viewed one of two television programs (about right-wing political independent, Pauline Hanson, and her emotive criticisms of Aborigines and Asian immigrants or about an ethnically-mixed group of young Australians and their positive sense of cultural identity), or they viewed no program (no contact control). Results indicated that both positive and negative media coverage of Australians affected Canadians' views of Australia in the short-term. In particular, negative coverage (of Hanson) promoted less favourable views of Australians and Australian race relations over time and relative to the positive media and no media control conditions. The media's role in shaping international images is discussed.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".