Classical Liberalism Meets the New Constitutional Order: A Comment on Mark Tushnet
Bibliographic record
Abstract
Judicial Role: Some Comparative Observations' offers a typology of judicial review that throws into high relief some of the key elements of any system of constitutional law.One key component of the mix is substantive: just what rights should, or does, a particular constitution protect?A second is structural: what payoff comes from assigning any particular level of constitutional protection to any particular right?The differences can matter.The United States Constitution simply invalidates the offending law.In contrast, the Canadian Charter of Rights and Freedoms provides that any such law can be reenacted for a five year period by a simple provincial majority.2 These two questions-of content and potency-are interdependent.Many modern constitutions reject the baseline of the United States Constitution, with its system of strong rights in property and liberty and strong judicial review.In contrast, newer constitutions offer weak protection to private property and often contain an impressive list of positive rights, such as the right to a decent job or decent housing.How does content influence potency?Tushnet begins his analysis of these knotty questions by looking at a number of Canadian cases.3 Historically, constitutions did not regulate relations between private individuals, but instead limited regulations to state actors.Yet as Tushnet notes,
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.037 | 0.033 |
| Insufficient payload (model declined to judge) | 0.006 | 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".