Social representation of palliative care in the Spanish printed media: A qualitative analysis
Bibliographic record
Abstract
BACKGROUND: Lack of social awareness is a major barrier to the development of palliative care. Mass media influences public opinion, and frequently deal with palliative care contributing to its image and public understanding. AIM: To analyse how palliative care is portrayed in Spanish newspapers, as well as the contribution made by the press to its social representation. DESIGN: Based on criteria of scope and editorial plurality, four print newspapers were selected. Using the newspaper archive MyNews (www.mynews.es), articles published between 2009 and 2014 containing the words "palliative care" or "palliative medicine" were identified. Sociological discourse analysis was performed on the identified texts on two levels: a) contextual analysis, focusing on the message as a statement; b) interpretative analysis, considering the discourse as a social product. RESULTS: We examined 262 articles. Politician and healthcare professionals were the main representatives transmitting messages on palliative care. The discourses identified were characterised by: strong ideological and moral content focusing on social debate, strong ties linking palliative care and death and, to a lesser degree, as a healthcare service. The messages transmitted by representatives with direct experience in palliative care (professionals, patients and families) contributed the most to building a positive image of this healthcare practice. Overall, media reflect different interests in framing public understanding about palliative care. CONCLUSION: The knowledge generated about how palliative care is reflected in the printed media may help to understand better one of the main barriers to its development not only in Spain, but also in other contexts.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".