Heidegger's fundamental ontology and the human good in Aristotelian ethics
Bibliographic record
Abstract
Abstract Neo‐Aristotelian ethical naturalists take the concept “human” to be central to practical philosophy. According to this view, practical philosophy aims at a distinctive human good that defines its subject matter. Hence, practical philosophy can survive neither the elimination of the concept nor its subsumption under a more general concept, such as that of the rational agent. The challenge central to properly formulating Aristotelian naturalism is: How can the concept of the human be specified in a way that captures the distinctive role that it is supposed to play in practical philosophy? For the view to be sustained, the concept “human” as it figures in practical philosophy must not designate rationality plus a set of facts that we learn empirically about ourselves and then consider from a detached standpoint of reason. Heidegger's existential analytic offers an approach to addressing the challenge to neo‐Aristotelian naturalism and, therefore, a way of capturing the sui generis human good. I aim to show that concepts of the existential analytic in Being and Time have their origin or parallels in readings of Aristotle and that they capture the distinctive character of the being that we are, exclusively, completely, and as a unity. I argue that fundamental ontology offers a way to grasp the integral unity and irreplaceability of the human that lies at the heart of the neo‐Aristotelian project.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| 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".