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Record W2303192471 · doi:10.5539/ass.v12n4p87

Can Academic Performance Enhance Group Membership and Leadership among Student Entrepreneurs in Malaysia?

2016· article· en· W2303192471 on OpenAlexvenueno aff
Isidore Ekpe, Norsiah Mat

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStratified samplingGovernment (linguistics)PsychologyDescriptive statisticsQuality (philosophy)Regression analysisFocus groupPublic relationsMedical educationPolitical scienceBusinessMarketingMathematics

Abstract

fetched live from OpenAlex

<p>This study examined the effect of academic performance on social group membership and future leadership among student entrepreneurs in Malaysia so as to enhance good quality leaders in the future. Underpinned to Blau’s social exchange theory, the study adopted survey method and proportionate stratified random sampling to collect data from 319 semester-5 university students from three public universities in Malaysia. Data analysis was done through descriptive statistics and regression methods. We found that high academic performance significantly and positively influenced future leadership among Malaysian student entrepreneurs. Therefore, the government and the universities management should initiate more advocacy programs to counsel students on the need to focus on their studies so as to earn better grades which would enhance their active participation in leadership activities after school. However, there was no evidence to prove that academic performance had any influence on group membership among the student entrepreneurs. The study was limited to university business students. Similar studies could be conducted on youths in other academic institutions such as secondary schools.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.343
Teacher spread0.287 · 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 teacher head, not a consensus.

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

Citations2
Published2016
Admission routes1
Has abstractyes

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