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Record W3195907511

Revolutionising the senate in Malaysia : lessons from Australia and Canada

2020· article· en· W3195907511 on OpenAlexaboutno aff
Mahyuddin Daud

Bibliographic record

VenueScientific Repository (Petra Christian University) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCommonwealth, Australian Politics and Federalism
Canadian institutionsnot available
Fundersnot available
KeywordsParliamentLegislaturePolitical scienceHouse of RepresentativesPublic administrationPoliticsPerceptionBenchmarkingLower houseLawManagementEconomicsPsychology
DOInot available

Abstract

fetched live from OpenAlex

Since its formation in 1959, the Senate has been seen as a less influential House of Parliament. Such perception is not distinct for Malaysia but also commonly found elsewhere. The Senate was designed to enable individuals with extensive professional experience to serve in legislature without contending in general election. It provides balanced and bipartisan insights from House of Representatives through participation from federal, states and special interest groups. With its influence being questioned, Senate’s relevancy continues to be debated. This paper explores two issues. Firstly, it analyses the perception of Senate as an irrelevant House of Parliament where Senators were accused for permitting political aspirations to take precedence above public interest. This led to the second issue where Senate was not independent in exercising its roles. In exploring the above, comparative analysis with Canada and Australia as potential models for benchmarking were made where suggestions are proposed.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0180.007
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.039
GPT teacher head0.257
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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