Coping with bereavement due to drug-related death in the context of one's own drug challenges
Bibliographic record
Abstract
Coping with a close relative’s drug-related death is an especially difficult and challenging process. If the bereaved family member is also using drugs, this has the potential to exacerbate these challenges, possibly with further consequences, some positive, some negative. This chapter focuses on this group, enquiring how bereavement reactions and grieving processes are altered as a result of also using drugs. Research is reviewed using data and published reports from projects across the United Kingdom, Norway, the Netherlands, the United States, and Canada. Although research in this area is still sparse, a tentative picture is emerging. The drug-relatedness of the death often leads the drug-using bereaved person to consider their own use in a different light. Sometimes, that may lead to a major change in their use (they may cut down or stop entirely, or they may increase their use to either cope with or avoid their grief). Often, ways of showing their grief are impacted by the stigma (and self-stigma) that the bereaved person perceives, related to either the person who has died or to themselves as a drug user: many find that their ability to grieve is seriously compromised. And for some, their view of death alters.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".