Bibliographic record
Abstract
Courts are called upon everyday to resolve disputes. Does that mean that they are the most appropriate forum for settling all types of cases? This article posits that they are not. It argues that courts are not suited to settling polycentric issues. Polycentric disputes are said to have numerous complicated, multifaceted, and unpredictable social and economic repercussions. In most cases, the settlement of polycentric issues requires significant expertise. They are therefore regarded as “unsuitable for judicial resolution”. Hence, adjudication is best appropriate for bilateral disputes over private claims of rights. It is least well-suited to disputes that implicate polycentric issues, which require a weighing of interests and the capacity to seek out and evaluate complex data. This is particularly true in environmental and natural resource cases. This article is part of a Wayne Law Review symposium volume commemorating the one hundredth anniversary of the Boundary Waters Treaty of 1909, between Canada and the United States. It examines the International Joint Commission (“IJC”), created by the Treaty, as a dispute settlement body and how it has resolved over 100 environmental disputes in since it was established in 1912. I posit here that non-court or non-adversarial dispute settlement bodies, such as the IJC, are better suited to resolving environmental and natural resource disputes than are courts. This because they offer the parties and the members of the “tribunal” the time and opportunity to delve into the issues, to employ technical expertise and to work towards a win-win outcome as opposed to the winner take all outcomes that are the necessary result in courts. In many respects these types of tribunals act like Masters that are appointed by United States federal courts pursuant to Fed.R.Civ.Pro. 53.
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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".