Bibliographic record
Abstract
SUMMARY Contemporary bioethics is confronted with a wide variety of serious challenges. Specialists in the theological and religious disciplines are increasingly involved in the bioethical debate. The author asks: Are there specific challenges posed to canon law in these discussions? Since the Church is an important provider of health care, it is surprising that there are not at least some general provisions in the Code. One response is that the Code provides for order and discipline in the Church. The Church provides norms and guidance for medicine and healthcare in other documents of the magisterium. The author suggests that it is inevitable that various bioethical questions will enter into the field of canonical reflection. Several major challenges which the biomedical sciences pose to both ethics and canon law are identified. The author analyzes several major scenarios and suggests how canon law can contribute to these discussions by drawing upon its rich history and helping to construct a response to these problems in the life of the faithful. The author also suggests that such participation in the debate is part of the mission of canon law itself, especially in assisting the faithful to achieve their salvation. This function is especially evident in the display of compassion and assistance in the resolution of conflicts, both personal and collective.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.027 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".