P-43 Dying matters week: using creativity to maximise audience reach
Bibliographic record
Abstract
<h3>Background</h3> Dying Matters Week is an awareness-raising week to encourage people to talk more openly about death. The aim of the week is to encourage a shift in attitudes to accept death as a natural part of everybody’s life cycle. <h3>Aims</h3> To run a creative campaign, on minimal budget, focusing on getting the wider general public to engage in discussion about death. To use humour to make the topic more accessible. To create a lasting legacy to carry on the conversation after the week has ended. <h3>Methods</h3> The campaign encouraged engagement by posing the question, <i>‘what’s your funeral song?</i>’ Staff and volunteers were polled on their favourite funeral song and a lip synch video created, filmed in a single take through the hospice, featuring staff and volunteers. Two events provided further reach to a non-medical audience. ‘<i>We need to talk about death</i>’, with Dr Kathryn Mannix, included quizzes, Prosecco and goody bag and was hosted by Virgin Radio DJ, Amy Voce. Using humour to tackle the taboo, comedian and actor Greg Davies was interviewed by Cariad Lloyd for a live edition of her award-winning podcast Griefcast. <h3>Results</h3> The events sold out. 100% attendees agreed to talk to friends and family about dying. The lipsync video was picked up by ITV Central and viewed 98,000 times, with 525 comments across all social platforms, 1872 likes, 795 shares. A hospice in Canada asked to use the video as part of their training. Griefcast podcast allowed us to leave a lasting legacy for the campaign. Extensive coverage in regional print and broadcast media. Its success has encouraged training to better equip more staff to talk to patients and families about dying. <h3>Conclusion</h3> Employing creativity in a public awareness marketing campaign can have a considerable impact on audience reach.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.067 | 0.019 |
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".