Bibliographic record
Abstract
Purpose To present the concept of moral invention as discussed by philosopher Paul Ricoeur and to examine how the selections operated by systems described by Niklas Luhmann as meaning‐constituting systems allow for the emergence of distinctions that would qualify as moral invention. Design/methodology/approach Ricoeur's philosophical position on ethics and morality is rooted in Husserlian phenomenology. So is Niklas Luhmann's description of meaning‐constituting systems and his discussion of their capacity to produce meaningful distinctions, including ethico‐moral ones. An interdisciplinary approach is used in order to highlight the conditions under which moral invention could become possible. In order to provide grounds for further discussions across disciplines, the extensive use of quotations is deemed necessary so that the material referred to can be traced back within Luhmann's extensive corpus, written and published in many languages. Findings Propositions are formulated as comments following the presentation of three of Luhmann's statements about meaning. These propositions indicate how meaning‐constituting systems could make distinctions or selections that would qualify as moral inventions. Originality/value To shows how second‐order cybernetics and philosophy, using as a common basis a description of meaning inspired by Husserlian phenomenology, can develop complementary propositions about ethics and morality.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".