Fair.com? An Examination of the Allegations of Systemic Unfairness in the ICANN UDRP
Bibliographic record
Abstract
Fair.com? reviews all 3094 ICANN Uniform Domain Name Dispute Resolution Policy (UDRP) decided through July 7, 2001 finding that that the allocation of cases may be unfairly biased toward trademark holders. It arrives at that conclusion based on three key findings. First, forum shopping has become an integral part of the UDRP. ICANN delegates the administration of the UDRP to four dispute resolution providers. Each provider maintains a roster of panelists who serve as judges in deciding the disputes. Complainants, who are invariably trademark holders, have the right to select which provider will handle their case. Track records of the various providers are a matter of public record and show that 90% of complainants rationally choose the two providers who feature panelists that render the most pro-complainant decisions. Second, there is a correlation between the selection of panelists and case outcome. UDRP cases are decided by either single or three-member panels. Single member panels feature one judge chosen exclusively by the arbitration provider. Three-member panels contain three judges selected by both the complainant and the respondent. This is significant since data shows that when providers control who decides a case, complainants win just over 83 percent of the time. As provider influence over panelists diminishes, such as in three-member panel cases, the complainant winning percentage drops to 60 percent. In an attempt to explain this, the study arrives at the third key finding - the higher winning percentage in single member panel cases may stem from provider bias toward ensuring that pro-complainant panelists decide the majority of cases. Although the allocation of cases is supposed to be random, the study finds that this may not be the case. For example, the National Arbitration Forum, one of the larger dispute resolution providers, has 135 panelists. However, 53 percent of its single panel cases are decided by only six of them. Those six panelists rule in favour of complainants 94 percent of the time. The article concludes that the solution to the forum shopping issue, and with it the concerns about bias and inconsistency within the UDRP, is surprisingly simple -- all contested UDRP actions should involve three-member panels. Establishing the three-member panel as the default would remove most provider influence over panelist selection and ensure better quality decisions by forcing panelists to justify their reasoning to their colleagues on the panel. As with the current system, both parties would play a role in selecting one panelist, who may be part of any ICANN-accredited providers' roster, while the provider would select the third panelist from among a list that both parties have reviewed and accepted.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.012 | 0.003 |
| Insufficient payload (model declined to judge) | 0.057 | 0.010 |
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".