Public Inquiries and the Legality of Blaming: Truth, Justice and the Canadian Way
Bibliographic record
Abstract
Accountability has become one of the major social concerns of the late twentieth century. Wide access to information by telecommunication is fuelling a hunger for knowledge about "what really happened" in relation to major events that cause significant suffering. Access to information has triggered a greater involvement by people in the way their countries and communities are run. Our society has a plethora of mechanisms with which to address individual and institutional accountability, many of them hidden from public view. The commission of inquiry is one mechanism that operates in full public view. The degree of political sophistication of the population means that "who did what to whom?" is no longer the only question that needs answering. Equally important are such related questions as: Who should be accountable to whom? By what standard should people in positions of responsibility be judged? What political and legal mechanisms enable us to best determine what really happened? What is the ultimate goal of any process of accountability? If some goals of an accountability process are incompatible with each other, how will we prioritize?
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 | 0.026 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.045 | 0.096 |
| Scholarly communication | 0.024 | 0.018 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.020 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 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".