You Don't Know What You've Got 'Til It's Gone: The Rule of Law in Canada - Part I
Bibliographic record
Abstract
The expression “rule of law” is multifaceted and entails a complex network of concepts. Although the expression is used frequently, its intended meaning is often connected to the context in which it is invoked. As the rule of law is so often used in a contextual manner, its conceptual underpinnings are often only partially understood and appreciated. The author examines the historicity of the rule of law and analyzes the concepts contained within the expression in order to give an explanation of their meaning, importance, and implications. A theme persisting throughout the article is that of the threats to the rule of law, both in general and in our Canadian context. An importance of the article is that the author, having provided the reader with an account of the rule of law, also provides the reader with the ability to appreciate, discern, and be vigilant against the threats to the rule of law. This article is Part I of a two-part series.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".