I CAN SEE CLEARLY NOW: VIDEOCONFERENCE HEARINGS AND THE LEGAL LIMIT ON HOW TRIBUNALS ALLOCATE RESOURCES
Bibliographic record
Abstract
Videoconferencing has generated ambivalence in the legal community.Some have heralded its promise of unprecedented access to justice,especially for geographically remote communities. Others, however, havequestioned whether videoconferencing undermines fairness. The authorsexplore the implications of videoconferencing through the case studyof the Ontario Landlord and Tenant Tribunal, which is one of thebusiest adjudicative bodies in Canada. This analysis highlights concernsboth with videoconferencing in principle and in practice. While suchconcerns traditionally have been the province of public administration,the authors argue that a tribunal’s allocation of resources and thesuffi ciency of its budget are also core concerns of administrative law.Administrative law reaches beyond conventional doctrines of proceduralfairness on the one hand and substantive rationality on the other. Howthe legislature structures and funds decision-making bodies is not just amatter of political preference but also of legal suffi ciency. The commonlaw, the Charter of Rights, and unwritten constitutional principles suchas the rule of law and access to justice all provide potential constraintsboth on governments and tribunals as to the organization and conductof adjudicative hearings, especially in settings like the Landlord andTenant Tribunal, where the rights of vulnerable people are at stake.While a challenge to the videoconferencing practices of the Landlordand Tenant Tribunal has yet to be brought, the authors conclude thateventually the intersection of tribunal resources with the fairness andreasonableness of that tribunal’s decision-making will reach the courts.How the courts resolve these challenges may represent the next frontierof administrative law.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".