Petisyen Parlimen: Penilaian tatacara petisyen Dewan Rakyat dan halatuju untuk merealisasikan sebuah Dewan Rakyat berteraskan Rakyat
Bibliographic record
Abstract
Parliamentary petitions are an established mechanism in legislative bodies around the world. Yet, the petitions procedures in the Malaysian parliament and its sub-national legislatures have not flourished. This study focuses on unpacking the petitions procedure in the Dewan Rakyat and impediments to its usability, by applying a two-level comparative analysis: first at the international level involving the UK House of Commons and Canadian House of Commons; and second at the sub-national level involving the state legislative assemblies of Selangor, Sarawak, and Sabah. This study identifies that existing rules do not provide sufficient clarification about the scope, format, and content of petitions including on vital features. The rules also do not clearly delineate the process for submitting, presenting, and deliberating petitions. This study concludes with recommendations to strengthen the procedure in the Dewan Rakyat so that the fundamental purpose of parliamentary petitions can be achieved, which is to provide a pathway for public participation in the parliamentary process.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".