Bibliographic record
Abstract
In their introduction to Law in the Domains of Culture , Austin Sarat and Thomas Kearns write: “[l]aw and legal studies are relative latecomers to cultural studies. To examine [law in the domains of culture] has been, until recently, a kind of scholarly transgression.” The same could be said in reverse: cultural studies (including anthropology) are a relative latecomer to law and legal studies, but in the last few decades there has been a striking irruption of cultural discourse in the domain of law. It is as if the acquisition of some degree of “cultural competence” has become a duty in legal circles. Not only are there seminars and courses in “cultural sensitivity” for judges, lawyers, and law enforcement officers, but “the culture concept” now informs many judicial decisions regarding Aboriginal rights, and “the cultural defense” (while hotly contested by some, and still lacking official approbation) has become a feature of numerous criminal trials involving immigrants. Interestingly, the Canadian Charter of Rights and Freedoms refers to “the multicultural heritage of Canadians”, and makes the preservation and enhancement of this heritage a condition of its own interpretation.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.032 | 0.007 |
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".