A scoping research literature review to explore bereavement humor
Bibliographic record
Abstract
The death of a loved one is extremely impactful. Although much of the focus now on helping people who are experiencing bereavement grief is oriented to distinguishing complicated from non-complicated grief for early pharmaceutical or psychiatric treatment, lay bereavement support comprises a more common and thus highly important but often unrecognized consideration. A wide variety of lay bereavement programs with diverse components have come to exist. This scoping research literature review focused on bereavement humor, one possible component. Humor has long been recognized as an important social attribute. Researchers have found humor is important for lifting the spirits of ill people and for aiding healing or recovery. However, humor does not appear to have been recognized as a technique that could benefit mourners. A multi-database search revealed only 11 English-language research articles have been published in the last 25 years that focused in whole or in part on bereavement humour. Although minimal evidence exists, these studies indicate bereaved people often use humor and for a number of reasons. Unfortunately, no investigations revealed when and why bereavement humor may be inappropriate or unhelpful. Additional research, multi-cultural investigations in particular, are needed to establish humor as a safe and effective bereavement support technique to apply or to use. Bereavement humor could potentially be used more often to support grieving people and bereaved people should perhaps be encouraged to use humor in their daily lives.
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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 | 0.019 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.039 | 0.024 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".