Media actors’ perceptions of their roles in reporting food incidents
Bibliographic record
Abstract
BACKGROUND: Previous research has shown that the media can play a role in shaping consumer perceptions during a public health crisis. In order for public health professionals to communicate well-informed health information to the media, it is important that they understand how media view their role in transmitting public health information to consumers and decide what information to present. This paper reports the perceptions of media actors from three countries about their role in reporting information during a food incident. This information is used to present ideas and suggestions for public health professionals working with media during food incidents. METHODS: Thirty three semi-structured interviews with media actors from Australia, New Zealand and the United Kingdom were conducted and analysed thematically. Media actors were recruited via purposive sampling using a sampling strategy, from a variety of formats including newspaper, television, radio and online. RESULTS: Media actors said that during a food incident, they play two roles. First, they play a role in communicating information to consumers by acting as a conduit for information between the public and the relevant authorities. Second, they play a role as investigators by acting as a public watchdog. CONCLUSION: Media actors are an important source of consumer information during food incidents. Public health professionals can work with media by actively approaching them with information about food incidents; promoting to media that as public health professionals, they are best placed to provide the facts about food incidents; and by providing angles for further investigation and directing media to relevant and correct information to inform such investigations. Public health professionals who adapt how they work with media are more likely to influence media to portray messages that fit what they would like the public to know and that are in line with public health recommendations and enable consumers to engage in safe and health promoting behaviours in response to food incidents.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".