Discourse - Ethical Challenges of the 21st Century: Attending to Relations
Bibliographic record
Abstract
A woman had a dream. In this dream she dreamt that Life stood before her and in her hands Life held two gifts _ in the one Love, in the other Freedom. Life asked the woman to choose. After a long deliberation, the woman finally chose Freedom. And Life said, 'Thou hast well chosen. If you hadst said, 'Love', I would have given thee that thou didst ask for; and I would have gone from thee, and returned to thee no more. But now, the day will come when I shall return. In that day I shall bear both gifts in one hand (Schreiner, 1890, pp. 99-100). Does Schreiner mean that with Freedom as the choice, Love is possible as well, while with Love only, there is a danger of losing Freedom? I am intrigued with such a proposal and tend to think that in health-care and nursing ethics, as in Life, we need both of Life's gifts. We need both freedom and love. We need the individual freedom to make decisions and choices for ourselves, and we need love and compassion for others within a community.
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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 | 0.048 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.042 | 0.164 |
| Scholarly communication | 0.035 | 0.038 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.019 | 0.024 |
| Insufficient payload (model declined to judge) | 0.006 | 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".