Best Practices in Administrative Decision-Making: Viewing the Copyright Board of Canada in a Comparative Light
Bibliographic record
Abstract
This report focuses on the decision-making process used by the Copyright Board of Canada for tariff setting. Previous reports have identified delays in tariff setting as a problem to be resolved. Drawing on the decision-making processes of comparable federal administrative tribunals and recent civil justice reforms in Canada, this report makes several recommendations as to how the Copyright Board could improve its tariff-setting process so as to bring the process into line with best practices in administrative decision-making. The general principles of administrative law, which provide the overarching legal framework in which any changes will be implemented, are also laid out.This report takes as given the current role of the Copyright Board and the resource constraints under which it operates, proceeding on the basis that additional funding will not be made available to the Copyright Board in the near future. Accordingly, the goal of this report is to provide the Copyright Board with additional tools that it can use to improve the efficiency of its decision-making processes. In this regard, this report notes that tariff-setting delays might be due at least in part to the attitudes and expectations of those who participate in the process, in which case the additional tools could usefully be used to effect a culture change in Copyright Board proceedings.In Section I, general background is provided about this report, which explains why the report was commissioned and lays out the context in which the report was prepared. In Section II, the role of the Copyright Board is explained, in order to better understand its current decision-making framework and the challenging environment within which it operates. In Section III, the general principles of administrative are laid out, with a view to explaining the framework in which the recommendations of this report can be implemented by the Copyright Board. In Section IV, the decision-making processes of comparable federal administrative tribunals (the selection of which is, in addition, justified) are laid out alongside the tariff-setting process of the Copyright Board. In Section V, the literature on Canadian civil justice reform, which aims at making court processes more efficient, is examined, with a view to formulating best practice recommendations for administrative tribunals. In Section VI, a general framework to guide the reform of administrative procedures is proposed, with particular reference to the need to give administrative decision-makers such as the Copyright Board the tools to effect culture change where attitudes and expectations of actors may cause inefficiency in the decision-making process.Sections IV, V and VI also form a coherent whole, starting with administrative processes in Section IV (with a view to ascertaining how the Copyright Board is placed relative to peer federal administrative tribunals) and moving to civil justice reform in Section V (with a view to drawing inspiration in the administrative context from judicial reforms), before finishing in Section VI with a discussion of the importance of culture (with a view to bringing the lessons learned in Sections IV and V into a theoretical best-administrative-practice framework).In Section VII, recommendations are made as to the procedural reforms that have the potential to reduce the time the Copyright Board takes to render tariff-setting decisions.
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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 | 0.036 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.024 |
| Science and technology studies | 0.054 | 0.043 |
| Scholarly communication | 0.056 | 0.012 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".