Conquering Media Coverage : The use of battle metaphors in hospital foundation communications and its impact on news coverage
Bibliographic record
Abstract
Battle terminology such as “fight,” “conquer,” and “hero” and imagery that compares doctors and patients to superheroes, soldiers and athletes have become increasingly prevalent in hospital foundation communications. The use of these metaphors has been highly controversial. While some audiences have praised foundation campaigns that use this type of messaging for emphasizing the strength of patients and hospital staff, encouraging patient families, and motivating patients to be resilient, others argue that these campaigns marginalize those who are unable to overcome their health conditions, positioning them as failures or losers. While the use of battle metaphors in hospital communications has been a heated topic in online discussion, little is known about the impact of this language on the media coverage and financial support that they generate for hospitals. This paper presents a multimodal discourse analysis of the communications of six hospital foundations in Toronto, Canada followed by a quantitative and sentiment analysis of the media coverage each foundation has received within the last fiscal year. The aim of this paper is to determine if there is a relationship between the use of battle metaphors in hospital foundation communications and the amount and sentiment of media coverage. According to agenda setting theory, media coverage has a palpable impact on public action. Therefore, the findings of this research may assist hospital foundations in developing useful communications practices they can employ to increase media exposure and, consequently, attract more donations to support their institutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".