Evolutionary approach in reasoning practice of constitutional justice
Bibliographic record
Abstract
The author examines the essence and characteristic features of the evolutionary interpretation in constitutional review bodies decisions and concludes given the relationship between processes of argumentation and interpretation, as well as definite characteristics and trends in the application of the evolutionary interpretation in different countries, that it is more appropriate to talk about the evolutionary approach in argumentation, not about a separate method of interpretation. An evolutionary constitutional interpretation, as it is stated in the article, does not necessarily mean going beyond the literal text of the basic law. A literal (textual) interpretation and an evolutionary approach are combined phenomena of different nature; they are allocated based on various criteria – the source (orientation on the text) and the socially adaptive result, respectively. The value of the evolutionary approach is associated with the possibility of “adjusting” constitutional norms to real social canvas without making changes to the text of a constitution. The author shows using the case law examples that an evolutionary interpretation can be expansive, that is aimed at increasing the scope of constitutional regulation (“filling” constitutional norms with “new” (additional) content, picking out new human rights, increasing their level of protection), and restrictive, that is narrowing the scope regulated and (or) protected by a constitution (reducing level of human rights guarantees or subject area of constitutional regulation). Considering through the prism of specific constitutional justice cases such doctrines as of a “living constitution” in the United States of America, a “living tree” in Canada and the concept of “judicial law development” in Germany, the author comes to the conclusion that an independent concept of the evolutionary approach in legal reasoning has not been formed yet in the Russian practice of constitutional justice. In this regard, it seems to be perspective direction to develop such a concept, especially in the context of a possibility of combining the evolutionary approach with original interpretation. It seems that despite the fact that the problem of judicial activism is not now a problem of current urgent interest in Russia, the constitutional amendments of 2020 have actualized the potential for an evolutionary interpretation of certain constitutional provisions.
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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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.045 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| 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".