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Record W4390585735 · doi:10.18646/2056.111.24-001

Harnessing the Power of the Stock Market for Social Good: Establishing an Islamic Social Stock Exchange in Malaysia

2024· article· en· W4390585735 on OpenAlexaboutno aff
Sharifah Nur Asilah Jasmine Syed Mohamed Noor Azmi, Aishath Muneeza

Bibliographic record

VenueInternational Journal Of Management and Applied Research · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamStock exchangeBusinessStock (firearms)Listing (finance)Qualitative researchPublic relationsPolitical scienceSocial scienceFinanceSociologyEngineering

Abstract

fetched live from OpenAlex

This research investigates the feasibility and implications of introducing an Islamic Social Stock Exchange (SSE) in Malaysia by drawing insights from global SSE frameworks. The objectives of the research are to: analyze the concept and framework of SSEs in the United Kingdom, Spain, Singapore, and Canada; identify the benefits and impact of SSEs on social and economic development; study the possible challenges in introducing an Islamic SSE in Malaysia; and explore the public's appetite and motives to invest in such an exchange. Employing qualitative research methods, such as literature reviews, surveys, and interviews, the study unveils a spectrum of SSE frameworks, highlighting their diverse positive impacts on social and economic development. Simultaneously, challenges emerge in the realms of Shariah compliance, listing fees, and public awareness. The findings not only underscore the practical significance of these insights but also emphasize their pivotal role in shaping the potential development of an Islamic SSE in Malaysia. This research contributes to enriching shared understanding of global SSE practices, fostering progress in Malaysia's social, economic, and environmental spheres.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.638

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.043
GPT teacher head0.330
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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