A Note of Appreciation
Bibliographic record
Abstract
A year-and-a-half ago, the Michigan Journal of Law & Society (MJLS) was only an idea.Like many of the best ideas, MJLS started out as a conversation between a student and a professor.Having greatly enjoyed the Early American Legal History course at the University of Michigan Law School and having written way too much for the final paper for that course, James Kirwan, Editor-in-Chief for the first Volume of MJLS, approached Professor Bill Novak about legal history journals that consider accepting student notes.When told that all of the existing legal history journals cater towards professional scholars and that there was more demand than could be met by the existing supply of peer-reviewed journals, James asked Prof. Novak if there would be value in starting a legal history-themed journal at Michigan Law.With an exuberant yes as a reply, James and Novak began formulating an idea that would soon branch out to include a path breaking, multidisciplinary approach to legal scholarship, one that combines the best features of both law-student-run journals and faculty-run, peer-reviewed journals.MJLS expanded to encompass all of the social sciences and humanities because of the great programs here at the University of Michigan, supported by many of the kindest and most energetic scholars and students anywhere in the world.Recognizing that student-run law journals necessarily limit their pool of knowledge to law students, and that we could better understand the law by seeing it from a greater number of disciplinary and methodological perspectives, Allie Goodman, Charlotte Smith, and *
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 | 0.012 | 0.111 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.021 | 0.015 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.088 | 0.128 |
| Insufficient payload (model declined to judge) | 0.021 | 0.013 |
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".