Bibliographic record
Abstract
Although the contributions made by public inquiries to the Canadian political process have been widely recognized, they have also received substantial criticism. In this paper, the author and, second, that they risk infringing the rights of inquiry witness who subsequently face criminal charges. Both of these criticisms relate to the exercise of coercive power by inquiries. The first criticism asserts that the elaborate procedures that accompany the exercise of coercive powers by an inquiry have become so extensive and ‘court-like’ as to make inquiries unwieldy. In response to the first criticism, the author argues that public inquiries have a continuing role to play in the Canadian political process. This is because an inquiry can deliver a level of thoroughness and independence that other public investigative processes cannot. The exercise of coercive powers, in particular, is an integral part of an inquiry’s capacity for credible fact-finding and forceful recommendations. This does not mean that an inquiry should be established whenever there is a political controversy. On the contrary, inquiries should be reserved for matters of grave public concern about an event that has had tragic or scandalous consequences.
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 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 | 0.078 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.014 | 0.087 |
| Scholarly communication | 0.023 | 0.018 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.044 | 0.044 |
| Insufficient payload (model declined to judge) | 0.005 | 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".