Bibliographic record
Abstract
Dementia Friendly initiatives are emerging around the world and many of them use a symbol or a brand to promote their activities. Some dementia advocates have highlighted the need for a Dementia Friendly symbol that has global recognition. The World Young Leader in Dementia (WYLD) have completed a scoping review of Dementia Friendly symbols currently in use around the world and collected attitudes towards the concept of developing a global Dementia Friendly symbol. Survey responses were received from 21 representatives of 16 countries, 15 of which have at least one Dementia Friendly initiative in place. A wide range of symbols are already in use. The concept of “not forgetting” can be found in symbols using the forget-me-know flower, the elephant and a knot. Three main colour groups are represented: orange (mostly in Asian nations), purple, (mostly in North America) and the blue/yellow combination (forget-me-not). No survey responders rejected the idea of a global Dementia Friendly symbol. Fewer people favoured a global symbol (29%) than a global theme or element (67%), i.e. a colour, logo or design that can be incorporated into existing symbols or adapted for different regions. A second consultation in April 2016 gave an opposite view, with 65% of responders favouring a global symbol and 28% favouring a global element or theme. A key reason for this difference could be a separation of views between nations that already have a well-established symbol and those that do not. Further results from WYLD’s scoping review will be presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.011 | 0.025 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".