Participating in Organ Donation: Issues Among Black South Africans
Bibliographic record
Abstract
The medical transplantation of human body organs remains the only efficacious therapy for patients who are confronted with the reality of death due to the breakdown of their vital body organs such as the heart, lungs, kidneys, pancreas, and liver. Nevertheless, their hopes of improving and prolonging their lives on earth are shattered by the consistent shortage and paucity of suitable organ donors. The scarcity of human organs is an issue of great concern in public health, both locally and internationally and the current outlook is bleak. This study seeks to explore factors that prevent black South Africans in Limpopo province from participating in organ donation. In a quest to explore factors that might impede black South Africans from participating in organ donation, a qualitative approach and explorative research design were used. Non-probability sampling was used to select 30 research participants. In-depths interviews were used to collect data and the data analysis method was a content analysis. The study was based on the theory of planned behaviour. The study established that the majority of black South Africans are not registered organ donors. A lack of awareness or educational, religious, and cultural backgrounds and myths regarding organ donation prevent black South Africans from registering and donating their organs. This study recommends further research into organ donation, and the development of a social work model to increase the awareness rate of organ donation in black communities. It calls for the evaluation of legislation that regulates organ donation and transplantation in South Africa.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".