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Record W1947447327 · doi:10.5539/ass.v11n24p153

Technical and Vocational Education in Malaysia: Policy, Leadership, and Professional Growth on Malaysia Women

2015· article· en· W1947447327 on OpenAlexvenueno aff
Nor Lisa Sulaiman, Kahirol Mohd Salleh, Mimi Mohaffyza Mohamad, Lai Chee Sern

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsnot available
FundersUniversiti Tun Hussein Onn Malaysia
KeywordsVocational educationContext (archaeology)Representation (politics)Political sciencePublic relationsProfessional developmentPopulationOrder (exchange)Economic growthSociologyPedagogyBusinessEconomicsGeographyPoliticsLaw

Abstract

fetched live from OpenAlex

Technical and Vocational Education (TVE) is facing new challenges in an increasingly competitive global context. The continuing under representation of women in engineering fields at semi-skilled and high-skilled levels is receiving renewed attention. This paper explores women as part of special population in Malaysia who desire to be placed as equal to men in Malaysian context. Policy, leadership, and professional growth are discussed comprehensively to support Malaysian females’ involvement in engineering disciplines, one of Technical and Vocational Education (TVE) programs in Malaysia. This paper also explores issues and challenges facing by Malaysian women in order to be recognized by the sub-ordinates, peers, leaders and society within male-dominated professions and environment.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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 designQualitative
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

Citations15
Published2015
Admission routes1
Has abstractyes

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