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Record W2160452040 · doi:10.5539/ass.v10n18p225

University Students and Voting Behavior in General Elections: Perceptions on Malaysian Political Parties Leadership

2014· article· en· W2160452040 on OpenAlexvenueno aff
Sivamurugan Pandian

Bibliographic record

VenueAsian Social Science · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
FundersUniversiti Sains Malaysia
KeywordsOpposition (politics)General electionStatus quoPoliticsPolitical scienceAllianceVotingSplit-ticket votingPolitical economyNational electionPosition (finance)PerceptionPublic administrationLawSociologyEconomicsPsychology

Abstract

fetched live from OpenAlex

Malaysia’s 13th General Election held on 5 May 2013 was one of the most exciting General Elections in Malaysia’s political history. The result showed that the ruling party Barisan Nasional (National Front) or BN and the opposition coalition Pakatan Rakyat (People’s Alliance) or PR contested closely in the 222 Parliamentary seats. Although the results showed a rather status quo in favour of the ruling party, the opposition coalition managed to increase their seats to 89 compared to 82 from the 2008 12th General Election while the seats obtained by the ruling party reduced to 133 from 140 seats. National Youth Survey by the Asia Foundation indicated that the political thinking of the youths in Malaysia are not static but have changed accordingly. This new shift allows this paper to discuss the position of the youth in Malaysia with a reference to the selected university students on Malaysian political parties’ leadership and which party will benefit from their role in Malaysian politics.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.059
GPT teacher head0.335
Teacher spread0.277 · 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 designObservational
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

Citations23
Published2014
Admission routes1
Has abstractyes

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