Bibliographic record
Abstract
ln this interdisciplinary research I will study the convergence of two phenomena intricately linked and highly topical of the late 20th and early 21st centuries: Regional Market Integration (RMI) and Alternative Dispute Resolution (ADR). Both in the literature and in the real world, RMI, which is premised on theories and policies of free trade, is perceived as the better economic arrangement. But what are the contours of the benefit of RMI? Can access to justice be construed as a non-tariff barrier to RMI trade (NTB)?I limit the scope of inquiry to the study of companies as the beneficiaries of RMI, focusing on the dichotomy of big versus small and medium size companies. l further limit the focus to address the process of justice (not substance) as it arises in the event of disputes among firrns. Cascadia, which is a trans-border region within the North Arnerican Free Trade Agreement (NAFTA 1992) is thus a natural candidate for such research.
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 | 0.007 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".