Bibliographic record
Abstract
Emmanuel Levinas is one of the great writers on ethics of the 20th Century, but he is little known in law. His two main works, Totality and Infinity and Otherwise Than Being, or Beyond Essence, offer a reconstruction of human selfhood away from questions of identity and ego and towards an ‘ethics of the other’. His writing is passionate, mystical, and rational, at times erudite and elsewhere downright obtuse. But as reward for this struggle, Levinas offers a sustained meditation on the relationship of ethics, responsibility and law, and - remarkably - he does so using the language of the duty of care. Here then is a philosopher, largely unknown to legal theory, who at last speaks the language of torts. Central to Levinas’ meditations is an idea of ethics to which I will have recourse. For Levinas, and those who have been influenced by him, the word ethics implies a personal responsibility to another that is both involuntary and singular. The demand of ethics comes from the intimacy of an experienced encounter, and its contours cannot therefore be codified or predicted in advance. At least as opposed to the Kantian paradigm of morality as ‘a system of rules,’ ethics therefore speaks about inter-personal relationships and not about abstract principles. At least as opposed to most understandings of law, ethics insists on the necessity of our response to others, and the unique predicament of each such response, rather than attempting to reduce such responses to standard instances and norms of general application applicable to whole communities and capable of being settled in advance. Indeed, ethics constantly destabilizes and ruptures those rules and that settlement. Furthermore, ethics implies an unavoidable responsibility to another which Levinas exhorts as ‘first philosophy’: by this he means to indicate that without some such initial hospitality or openness to the vulnerability of another human being, neither language nor society nor law could ever have got going. At least as opposed to many understandings of justice, there is nothing logical or a priori inevitable about such an openness; except that without it, we would not be here to talk to one another. We cannot derive this ethics from rational first principles. Ethics is that first principle.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.048 |
| Scholarly communication | 0.012 | 0.016 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".