Bibliographic record
Abstract
Abstract Before we go further in developing an understanding of the common law, it will be useful to contrast its methods with those of the civil law. The identity of “civilian lawyers” is born when they go abroad. It is a little like being an “African.” Only when the Kenyan or Nigerian (or, the Kikuyu or Yoruba) comes to another continent does she begin to think of herself as an African. The same thing is true of lawyers in Italy, Spain, France, Germany, Korea, and Japan. The sense that they all belong to the same “legal family” is acquired when they leave their homeland and confront the other family, the common law. The Francophones of Québec think of themselves as adherents of the “civil law” only because they are confronted on a daily basis with the “other”—the Anglophone common lawyers. But the Germans and French and Spaniards read few contemporary books about the “civil law” and do not use a term in their respective languages to refer to themselves as “civil lawyers.” Their common identity is geographical, not legal. They think of themselves most likely as Germans, French, or Spaniards or, increasingly, as “Europeans”— perhaps as “Continental Europeans” to distinguish themselves from the English, Scots, and Irish.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".