Bibliographic record
Abstract
Labour law historians rarely write about the theoretical and methodological foundations of their discipline. In response to this state of affairs, this article adopts a reconnaissance strategy, which eschews any pretense at providing a synthesis or authoritative conclusions, but rather hopes to open up questions and paths of inquiry that may encourage others to also reflect on a neglected area of scholarship. It begins by documenting and reflecting on the implications of the fact that labour law history sits at the margins of many other disciplines, including labour history, legal history, labour law, industrial relations and law and society, but lacks a home of its own. It next presents a short historiography of the writing of labour law history, noting its varied and changing intellectual influences. Next the article notes some of the methodological consequences of different theoretical commitments and discusses briefly the possibilities opened up by computer technologies as revealed by two interesting projects that rely heavily on the construction of sophisticated data bases. Finally, the article reflects on the methodological challenges the author has experienced in his current project on labour law’s recurring regulatory dilemmas and conclude with some thoughts on the contribution labour law history can make to our understanding of the dynamics that shape the law's current challenges.
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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.009 |
| 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".