MétaCan
Menu
Back to cohort
Record W2959183829 · doi:10.5430/rwe.v10n2p30

Identifying the Challenges of the Sarawak Malay Terubok Ikan Masin (Salted Fish) Entrepreneur: Qualitative Study

2019· article· en· W2959183829 on OpenAlexvenueno aff
Jati Kasuma, Niena Nurul Farhana, Hazami Mohammad Kamaruddin, Muhamad Saufi Che Rusuli, Yusman Yacob

Bibliographic record

VenueResearch in World Economy · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMalayTourismBusinessFish <Actinopterygii>Qualitative researchMarketingFisheryGeographySociologySocial scienceBiology

Abstract

fetched live from OpenAlex

Sarawak Malay entrepreneur of terubuk ikan masin has become one of the successful entrepreneurs in the entrepreneurial field. Even though the number of the entrepreneurs are still small, but the Sarawak Malay entrepreneur of terubuk ikan masin become one of the main contributor to the state tourism activities. Hence, those entrepreneurs still have to face a lot of challenges and obstacles in the business. Thus, this research aims are to identify the challenges faced and the framework with regards to the challenges faced by the Sarawak Malay entrepreneur of terubuk ikan masin. Using qualitative study to understand the challenges that they are faced in line with this business and finding shows the challenges they faced both personally and in business itself during the various stages of business development are location not strategic, economy problem, lack of business knowledge and financial support. Moreover, Sarawak Malay entrepreneur terubuk ikan masin also plays an important role in economic development and income growth because terubuk ikan masin is one of the best products in Sarawak besides multilayer cake. Terubuk ikan masin gives contribution especially in eco-tourism. Hence, these terubuk ikan masin are important estuarine fishes, both commercially and culturally in many Asian countries, including Malaysia. The information that generated from this research will be useful for further studies not only for the future researcher but also for sustainable on commercial fish.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.194
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.101
GPT teacher head0.361
Teacher spread0.260 · 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.

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

Citations2
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueResearch in World EconomySame topicIslamic Finance and Banking StudiesFrench-language works237,207