Bibliographic record
Abstract
In this focus feature, David Trubek and Michael Trebilcock present an assessment of the past forty years of the law and development movement and map the challenges that lie ahead. While law and development research today seems to be on more solid ground than it was in the late 1960s and early 1970s, it is still at risk of facing a second demise. The recent revival of the law and development movement has been marked by a research agenda increasingly attuned to the importance of local context. On the one hand, contextualization has countered the ethnocentric analysis produced in the Global North and exported to developing countries in the 1960s. On the other hand, attention to context has caused a severe fragmentation of the academic dialogue, as the concern with adaptation to particular circumstances defies any attempt to somehow connect these research efforts in one single conceptual framework. The new generation of law and development scholars is thus left with the challenge of maintaining contextualization, while avoiding letting the movement break down into a ‘series of self-referential silos.’
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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.051 |
| Scholarly communication | 0.020 | 0.023 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".