Transnational Legal Discourse: Reflections on My Time with the German Law Journal
Bibliographic record
Abstract
By October 2013, the German Law Journal, published monthly and available at no cost on the Internet – www.germanlawjournal.com – counted approximately 1593 publications, authored by approximately 1.450-1.500 authors. A journal project of such magnitude in itself could certainly not have been expected by its founders. Just as unlikely it would have seemed to them or anyone else, for that matter, that their little, bi-monthly email newsletter, originally entitled “Momentaufnahme” (Engl.:snapshot; French:glimpse d'oueil), would grow into a web-based, peer-reviewed legal periodical with more than 13.000 registered subscribers worldwide and a sizable journal ranking among existing international law reviews. If I only had a moment to express my thoughts on leaving the Journal, I would use it to express my immense gratitude to those whom I can never thank enough. My colleagues in this project, present and former members on the editorial board, and the authors, from near and far, many of whom we never had the fortune to meet in person despite an often vivid exchange of thoughts and ideas, as well as, of course, our readers throughout the years – it is to all of them that I owe thanks too comprehensive to measure. It is one thing to launch a journal, it is another for it to be read, sustained, shaped and encouraged over the span of almost fifteen years. The GLJ is what it is today because of the input it has received over all this time, and for that I am immensely grateful.
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 | 0.022 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.041 | 0.047 |
| Scholarly communication | 0.041 | 0.026 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.008 | 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".