The Influence of Liberty Concepts on the Legal Classification of Constitutions and Constitutional Governments
Bibliographic record
Abstract
Due to global developments in constitutional law and especially the importance of principles of republicanism, the sovereignty of the people and the protection of individual rights and public liberties as the foundations of constitutionalism and constitutional government, it seems that a new category of constitution that is consistent with the principles and foundations of constitutionalism and the constitution should be provided. Therefore, the classical categories of constitutions are briefly introduced and then their unlawful aspects will be criticized and then, new categories of constitutions are introduced and described. This classification is based on the assumption that republic governments can be constitutionality and with a focus on the protection of liberty can use its power without being required to comply with liberty in its liberal concept. So as constitutions can be divided into two types of liberalism and republicanism, governments can be classified into two types of Republicanism and liberalism too. Since the classic categories have acted based on inductive method, therefore, this method has been used to criticize and propose alternatives.
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 | 0.030 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.005 | 0.047 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".