You will always be with me: an exploration of the prevalence and perceptions of memorial tattoos
Bibliographic record
Abstract
Memorial tattoos are an increasingly common personal act of remembrance. This study investigated the prevalence and perceptions of memorial tattoos through an online questionnaire. A sample of 306 participants (245 women, 34 men, and 27 unspecified) with a mean age of 31.50 years (ranging from 19-75) voluntarily participated in the study. While 52.6% of the participants reported having a non-memorial tattoo, 18.3% reported having a memorial tattoo. Overall, the perceptions of memorial tattoos were more positive than non-memorial tattoos, with 96.3% receiving positive feedback, compared to 79.7% for non-memorial tattoos. Participants perceived memorial tattoos as less disturbing, less stigmatized by society, and more acceptable in the workplace compared to non-memorial tattoos. Participants perceived people with memorial tattoos as less likely to participate in risky and unhealthy behaviours than those with non-memorial tattoos. Grieving participants were significantly more likely to agree that memorial tattoos were an appropriate way to remember a deceased loved one than participants who were not currently grieving. Participants who were grieving and had a tattoo agreed portraits were more acceptable for memorial tattoos than participants who were grieving and did not have a tattoo. Memorial tattoos were perceived more positively than non-memorial tattoos, and the characteristics of having a tattoo or currently grieving the death of a loved one further improved these perceptions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".