A relativistic approach to moral judgment in individuals: Review and reinterpretation
Bibliographic record
Abstract
Abstract In Ethics Position Theory, relativism is the degree to which people believe that universal moral rules should not always be applied unwaveringly. Researchers often predict that highly relativistic individuals are characterized by questionable ethics given their ostensible self‐interested “anything goes” approach. Corroborating evidence for such predictions, however, remains elusive. This paper suggested that high relativists are perhaps not unethical, and reviewed four decades of relevant literature in order to clarify the meaning and implications of the relativism construct. The portrait of relativism that emerged is often contrary to prevalent expectations. Relativistic individuals seem tolerant of ambiguity, open to experience, non‐authoritarian, accepting of others with different backgrounds and lifestyles, and troubled by injustice. No persuasive evidence of questionable ethics is available. These findings have profound implications for managerial practice and suggest that highly relativistic employees may be among the most valuable. Future research grounded in an understanding of what relativism is rather than what it should be has the potential to allow a deeper understanding of this important construct to emerge. We also explore possible reasons why an inaccurate narrative about relativistic orientations may have emerged and persisted among both researchers and people generally.
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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 | 0.013 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".