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Record W2022593165 · doi:10.5539/ass.v10n2p202

Rural Malay Involvement in Malaysian Herbal Entrepreneurship

2013· article· en· W2022593165 on OpenAlexvenueno aff
Kamal Chandra Paul, Azimi Hamazah, Bahaman Abu Samah, Ismi Arif Ismail, Jeffrey Lawrence D Silva

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsnot available
Fundersnot available
KeywordsMalayEntrepreneurshipGovernment (linguistics)BusinessFocus groupEconomic growthQualitative researchRural areaSocioeconomicsTraditional medicinePolitical scienceMarketingMedicineSocial scienceSociologyEconomicsFinance

Abstract

fetched live from OpenAlex

Rural entrepreneurship is recognized as a primary engine of economic growth. The government of Malaysia is trying to increase the number of successful rural Malay herbal entrepreneurs nationwide. Therefore, the purpose of this study was to explore the involvement among rural Malay youth in herbal entrepreneurship in Malaysia. A qualitative approach using case study in-depth interview was used to gather data from ten rural herbal entrepreneurs. This study showed that in general Malay entrepreneurs are increasing gradually but technical based entrepreneurship is very low. It is suggested that the authorities of rural herbal development planners, government-link companies and other authorized agents need to focus on issues related to human capital, technical knowledge know-how and financial resources to increase the involvement of rural Malay youth herbal entrepreneurs.

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)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.237
Teacher spread0.222 · 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

Citations14
Published2013
Admission routes1
Has abstractyes

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