Protecting Human Rights and Constitutional Law in Bicameral Systems
Bibliographic record
Abstract
Background and objective: The second legislative chamber has played different roles and functions since its formation in ancient Rome and Greece. The philosophy behind the presence of this chamber (either in Federal systems or unitary systems) was a matter of controversy between its proponents and critics. There are more than 78 countries with two legislative chambers in the world. Protecting constitutional law and human rights are two notable functions of the second chambers. Research method: This paper used the descriptive–analytical method. The methods used by some second chambers are discussed as an example. Results (findings): how a second chamber can be considered as the scout of constitutional law and protector of human rights with regard to their normative behavior depends on the structure of the constitutional law. The role of the second chamber in protecting constitutional law is manifested in several forms: coinciding the bills and laws with constitutional law, amending and revising the constitutional law, vetoing or suspending bill a general appointments. Second chambers have several solutions including establishing the human rights committee with various duties. Therefore, these two criteria seem to be useful in order to measure the extent of democracy. Conclusion: A powerful second chambers are needed to make decisions, have the authority to amend the laws, and to have effect on the politics to realize human rights and protection of Constitutional law. It can also act as a human rights watch with regard to the nature of the norms of human rights.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".