A critical history of individual and collective ethics in the lineage of Lellouch and Schwartz
Bibliographic record
Abstract
The notions of individual and collective ethics were first explicitly defined in the biostatistical literature in 1971 to motivate a mathematical solution to a posed ethical dilemma. This paper reviews key antecedents to these concepts and traces explicit references to them over time, primarily in the biostatistical literature. Following a historical exposition of these texts, a critical thematic analysis shows the following: the normative force of these concepts has not been adequately argued. Individual and collective ethics do not solve the problem of how to use accumulating data to inform ethical action. The notions of the "individual" and the "collective" are too vague to prompt clear moral imperatives, especially in difficult cases. These concepts have not been successfully linked to a standard ethical framework. Finally, the paper concludes with the observation that a systematic, comprehensive ethical framework must be identified to fulfill the intuitions behind individual and collective ethics.
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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 | 0.143 | 0.884 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".