Bibliographic record
Abstract
When it comes to potential children, is to love them to leave them be (nonexistent)?I examine the possibility of virtuous reproduction, as well as some more basic theoretical issues surrounding the nature of moral goodness and obligation generally.Currently, there is a large body of literature in the field of reproductive ethics on questions of what considerations and practices ought to guide reproductive decisionmaking.The appropriate use of testing technologies to inform such decision-making, for instance, has been widely debated.Much smaller and less visible is the debate surrounding the prior question of whether reproduction itself is morally appropriate or desirable.I am particularly interested in how consequentialist strategies for including considerations of beneficence in reproductive decision-making have shaped moral approaches to reproduction.The principle of procreative beneficence (PPB), which mandates potential reproducers to select the best possible child, highlights the problematic nature of these strategies.The limited conceptual resources and problematic normative foundations of such strategies have stymied the development of a robust discussion on the ethics of reproduction itself.Other types of ethical approaches, loosely defined as deontological, offer superior accounts of what is at issue in reproduction, but also draw on some flawed background assumptions regarding, for instance, the nature of the moral agent and the scope of the moral sphere.The question of the morality of reproduction itself thus leads to an examination of far more basic issues in ethical theory: namely, the significance of meta-ethical commitments, and the desirability of a normative framework that offers a rich and agent-focused account of moral goodness and badness.I therefore argue that a virtue-centred ethics, grounded in neo-Aristotelian naturalism, iii accomplishes just that.And it is well-equipped to provide a meaningful and helpful analysis of the morality of reproduction, both holistically, in terms of the potential virtuousness of reproduction generally, and in terms of how the virtues of courage and benevolence may be expressed in reproduction.I conclude that a virtue-centred assessment of reproduction offers a sound and practical form of evaluation and that a virtuous character may indeed be expressed through reproduction.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".