Organ allocation and patient responsibility: Re-examining the concept of responsibility in light of the thought of Emmanuel Levinas.
Bibliographic record
Abstract
A persisting, unresolved debate in the bioethics literature was the impetus behind this work. The focus chosen was the need for replacement organs for those whose illnesses appear to be related to addiction to alcohol or tobacco. The initial section thus examines the more factual aspects of both addiction and organ transplantation. The history of organ transplantation is explored, focusing particularly on the attempts to frame criteria for reception of the scarce organs, and the concomitant attempts to increase the supply of donated organs; neither issue has been solved, although there is much research being focused on technical solutions in particular, for those awaiting scarce organs. Within the bioethics literature, the issue of criteria for the reception of scarce organs has tended to be viewed as a question of justice. Thus this work peruses the varying conceptions of justice which appear within that literature, in an attempt to ascertain whether their applications have involved differing results for the population in question. In fact, there appears to be little difference in the outcomes amongst those ascribing to one or other of the meta-ethical theories. In contrast to the extensive treatment of issues of justice within bioethics, the concept of responsibility is largely unexamined. This dearth suggested that an historical perusal of the concept of responsibility within a number of the disciplines to which bioethics turns would be appropriate. In the end, the thought of Emmanuel Levinas appeared to offer the most fruitful approach to the topic under consideration. His work appears to be a profound challenge to rethink our relationships to others, as well as our approach to justice. Central to that thought is what Levinas calls the relationship of the one-for-the-other; the philosopher suggests that a response of profound responsibility for the other before one is called forth by the visage of that "wounded" other. The question of justice does arise for Levinas, since in the eyes of the other before one are all the others; thus needs must be weighed and choices made. The benchmark for this justice, however, is the relationship of the one-for-the-other: real justice implies, not a faceless, objectified totality, but an attention to the needs of all---the very antithesis of the utilitarian approach so prevalent within much of North American bioethics. (Abstract shortened by UMI.)
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".