INCREASED ACCESS MEANS DECREASED FORMALITY IN MEDIATION
Bibliographic record
Abstract
One of the greatest advantages of the “digital turn” in mediation, touted by many, is the increased access it can provide to users of mediation. That access could include a person with a disability who need not travel to places that are inconvenient or inaccessible or a busy single parent who can now mediate from their homes. There is no question that digital mediation can allow more people to participate. A disclaimer: this paper does not discuss the many users who might not have access to consistent or high-quality internet access or a device that allows them to access the internet. Even where users have such access, there are some negative side effects to the “digital turn” in mediation and of this increased access; a main one is an associated decrease in formality—at least in non-commercial settings. Decreased formality can lead to decreased engagement in the process, an increase in inflammatory language, an increase in in-group vs. out-group conflicts within the session, acceptance of less fair outcomes by the side with less power, and a greater likelihood that parties will end the process with little or no notice. Professor Delgado was one of the first writers to note that mediation provides a less formal, and therefore potentially less fair process, particularly in divorce mediation and arbitration. Taking mediation online has increased those dangers, some, including Professor Ebner, have written on the potential dangers of the digital mediation process. This paper will explore those dangers and some possible means to attenuate them in the digital world. Some of those means include ways to increase trust, build rapport, and minimize misunderstandings and dishonesty, to ensure that increased access does not become a decrease in the quality of mediation or lead to less fair outcomes for users of mediation in the digital turn.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".