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Record W1978917166 · doi:10.5539/ijef.v2n3p199

Superiority of Conventional Banks & Islamic Banks of Bangladesh: A Comparative Study

2010· article· en· W1978917166 on OpenAlexvenueno aff
Md. Safiullah

Bibliographic record

VenueInternational Journal of Economics and Finance · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSolvencyProfitability indexMarket liquidityFinancial systemBusinessIslamProductivityFinanceEconomics

Abstract

fetched live from OpenAlex

The commercial banking system dominates the financial sector with limited role of non-bank financial institutions and the capital market. The Banking sector alone accounts for a substantial share of assets of the financial system. Commercial banks contribute significantly in the economic development through the development of major contributory economic indicators directly or indirectly. Commercial banks in Bangladesh operate under branding of interest-based conventional banks and interest-free Islamic banks (based on Islamic sariah).The study emphasis on the financial performance analysis of both stream of banks to measure superiority. The study indicates that financial performance (business developments, profitability, liquidity and solvency, commitment to economy and community, efficiency and productivity) of both streams of banks is notable. Study result based on commitment to economy & community, productivity and efficiency signifies that interest-based conventional banks are doing better performance than interest-free Islamic banks. But performance of interest-free Islamic banks in business development, profitability, liquidity and solvency is superior to that of interest-based conventional banks. That is comparatively Islamic banks are superior in financial performance to that of interest-based conventional banks.

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)0.002
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 score0.008
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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

Citations55
Published2010
Admission routes1
Has abstractyes

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