Public Understandings of the Definition and Determination of Death: A Scoping Review
Bibliographic record
Abstract
Background: Advances in medicine and technology that have made it possible to support, repair, or replace failing organs challenge commonly held notions of life and death. The objective of this review is to develop a comprehensive description of the current understandings of the public regarding the meaning/definition and determination of death. Methods: This scoping review was conducted in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Online databases were used to identify articles published from 2003 to 2021. Two reviewers (S.S. and K.Z.) screened the articles using predefined inclusion and exclusion criteria, extracted data for specific content variables, and performed descriptive examination. Complementary searches of reference lists complemented the final study selection. A search strategy using vocabulary of the respective databases was created, and criteria for the inclusion and exclusion of the articles were established. Results: Seven thousand four hundred twenty-eight references were identified. Sixty were retained for analysis, with 4 additional references added from complementary searches. A data extraction instrument was developed to iteratively chart the results. A qualitative approach was conducted to thematically analyze the data. Themes included public understanding/attitudes toward death and determination of death (neurological determination and cardiocirculatory determination of death), death and organ donation, public trust and legal variability, and media impacts. Conclusions: This review provides a current and comprehensive overview of the literature related to the general public's understanding and attitudes toward death and death determination and serves to highlight the gaps in this topic.
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 | 0.043 | 0.168 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".