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Record W2555466746

The Relationship between Traditional as well as Modern Modes of Financial Instruments for International Market through Islamic Finance

2016· article· en· W2555466746 on OpenAlexvenueno aff
Malik Shahzad Shabbir, Muhammad Saarim Ghazi, Tahir Akhtar

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamSukukFiqhRentingEquity (law)DebtFinancial instrumentFinanceUsuryIslamic financeBusinessHarmony (color)Islamic bankingGeneral partnershipBondEconomicsShariaLawPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Islamic financial system compared to western conventional system is related to the religion of Islam. The principles of Islamic finance are based on three main factors which are mentioned in the Quran and are an important part of Islamic jurisprudence, such as Riba, Gharar and Maysir. Islamic commercial law is based on three modes which serve as the basic blocks for complex financial products. These three modes are partnership based, trade based and rental based modes of financing. These three traditional modes of financing are dependent upon the size and limitations of entire market and desires of their target customers. The modern modes of financing consist upon Islamic Insurance (Takaful), Islamic financial derivatives, Islamic bonds (Sukuk) and Istisna. Furthermore, there should not be pure economical interest in transactions; it must contribute to the social harmony. It shows balanced between equity and debt and the trade of debt must be avoided which is explicitly expressed in the pillars of Islamic banking.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0050.004
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.001

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 head0.036
GPT teacher head0.255
Teacher spread0.219 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Internet Banking and CommerceSame topicIslamic Finance and Banking StudiesFrench-language works237,207