Bibliographic record
Abstract
Though many have tried to capture the place of mediation in the United States, the evolution of this process continues. Indeed, the process called ‘mediation’ can vary substantially within the United States, depending upon the preferences and skills of individual mediators, the demographics and norms of geographic regions, the cohesion and norms of the relevant legal and business communities and the resources dedicated by courts and agencies to identifying and fostering best practices among mediators. The same diversity of development seems to be true in Canada. Drawing upon available information regarding non-family civil court-connected mediation in the United States and Canada, this chapter will describe two general approaches - essentially, a bi-modal pattern - in the institutionalization of mediation. The first approach focuses on mediation primarily as an instrumental means to settle cases, thus clearing courts dockets and making more efficient use of parties’ and courts’ time and money. Courts devote few resources to the mediation programmes dominated by this approach, and the mediators and programmes seem to adapt to the settlement expectations and dispositions of the repeat players in the system - the lawyers and insurers. The second general approach to the institutionalization of mediation also assumes the process will settle cases, but expects it to achieve more - for example, ensuring that parties feel heard, allowing them to discuss relevant but non-legal concerns and underlying interests, urging lawyers to counsel their clients so that they can make informed, voluntary decisions and so forth. The court and agency programmes dominated by this second approach are much more likely to allocate the resources needed to develop cohesive communities of mediators with shared norms and practices. Further, these courts and agencies are more likely to expect lawyers to adapt to organizational preferences regarding appropriate participation in and objectives and mediation. Because there is a substantial relationship between court-connected mediation programmes and privately provided mediation services in the United States, it seems quite likely that the two approaches described here also exist in the private sector. The first approach is more likely to characterize the mediation of high-volume, small-value cases, as well as cases in which insurers’ participation is viewed as a wholly satisfactory substitute for the participation of individual or corporate defendants. The second approach, meanwhile, is more likely for public policy and large commercial matters in which the parties appreciate and engage in substantial preparation and the process adaptation needed to respond to the unique needs of the parties and their situations.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.013 |
| Science and technology studies | 0.018 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".