Community mediation: Reflections on a quarter century of practice
Bibliographic record
Abstract
Abstract It is fitting that this issue of Mediation Quarterly, one of the last before it transforms into a joint publication of confederating organizations, is devoted to community mediation. During the past twenty‐five years, community mediation has provided much of the momentum for the growth and diversity of the alternative dispute resolution movement in the United States. At the same time, it has faced many challenges as the larger dispute resolution field grows and evolves. How community mediation responds to these challenges will shape its role and place for the next generation. In this issue, we have asked some key leaders and practitioners in the field to reflect on the development of community mediation and the challenges as we move into another century of practice.
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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 | 0.120 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.027 | 0.108 |
| Scholarly communication | 0.026 | 0.035 |
| Open science | 0.006 | 0.025 |
| Research integrity | 0.029 | 0.034 |
| Insufficient payload (model declined to judge) | 0.009 | 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".