Mediating Ethically: The Limits of Codes of Conduct and the Potential of a Reflective Practice Model
Bibliographic record
Abstract
Discussions regarding the appropriate ethical behaviours for mediators and the subsequent development of formal codes of conduct have focused on hallmark issues such as third party impartiality and party self-determination. However, in an informal process, ethical choices are inherent in every intervention made by a mediator. In adopting the standard-setting approach of an adjudicative model, mediator codes of conduct are a poor fit with the conceptual and structural characteristics of this fluid, uncertain, and essentially private process. Confining the substantive and conceptual debate over mediation ethics to formal codes dangerously underestimates both the scope and the significance of choices faced constantly by intervenors in their process management role. A disclosing and questioning dialogue among mediators and others, using Schönian principles of reflective practice, is proposed as a more candid and complete recognition of the ethical dilemmas that arise in mediation. Two real-life case studies drawn from the writer's experience are used to illustrate this approach.
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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 | 0.199 | 0.216 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.013 | 0.163 |
| Scholarly communication | 0.034 | 0.047 |
| Open science | 0.008 | 0.020 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 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".