Bibliographic record
Abstract
This paper explores the implications of the idea of a constitution appropriate to a liberal-democratic state for the law of self-defence. The law governing self-defence, like other laws, must also a test of substantive legality appropriate to the constitution: it must be one that could not reasonably be rejected by a person who is a member of a civil condition created with the purpose of curing the insecurities of the state of nature. While this test of substantive legality is insufficiently powerful to determine all the details of the law of self-defence, it does have several important implications. First, the positive law must recognize a right of self-defence in the core case where the defender responds with necessary and proportionate force to a wrongful threat; second, the positive law must also provide at least an excuse leading to acquittal where the defender is reasonably mistaken about one of the conditions in the core case. Furthermore, the positive law must acquit a person who uses necessary and proportionate force to repel an innocent threat because the civil condition can provide no reason for punishing such a person.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".