A Scoping Review of the Literature on Public Solicitations for Living Organ and Hematopoietic Stem Cell Donations
Bibliographic record
Abstract
INTRODUCTION: Evolving methods of communication have increased public appeals for living organ and hematopoietic stem cell donations from strangers, giving public solicitations more visibility. Within the academic literature, perspectives have been divisive, reflecting ethical justifications for and against appeals for living unrelated donors. Transplant programs and clinicians face a variety of ethical dilemmas when patients and their solicited donors present to the hospital. OBJECTIVE: A scoping review methodology was designed to (1) explore the academic literature and (2) summarize and disseminate key research findings. METHODS: We used the Arksey & O'Malley framework for conducting and reporting scoping reviews and to review the prominent ethical arguments, counterarguments, and policy implications in the literature. From 4616 articles identified through MEDLINE, EMBASE, PsycInfo, and CINAHL, we screened titles and abstracts to assess eligibility for full-text review. RESULTS: We retrieved 280 full texts, extracted data from 61, and coded and analyzed 41 papers. Of these, 36 were from or based in the US context. Two articles originated from Canada. Three articles addressed public solicitations of hematopoietic stem cell donation. We mapped themes under 3 major headings related to public solicitations of living unrelated donors for organs and hematopoietic stem cells: (1) interpretations and modes, (2) ethical arguments for and against, and (3) policy implications and suggestions to address challenges for clinical practice. DISCUSSION: The academic literature contains divisive perspectives of public solicitations for organ and hematopoietic stem cell donation, each of which deserves further reflection for implications for policy and practice.
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 | 0.036 | 0.183 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.045 | 0.051 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".