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Record W2913470903 · doi:10.5539/ibr.v12n2p165

Microfinance Institutions: It’s Role in Palestine Economic Development

2019· article· en· W2913470903 on OpenAlexvenueno aff
Sharif Abu Karsh, Anan Y. Deek

Bibliographic record

VenueInternational Business Research · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsMicrofinancePovertyPoverty reductionPalestineObjectivity (philosophy)BusinessEconomic growthState (computer science)Development economicsEconomics

Abstract

fetched live from OpenAlex

Microfinance is a tool for state poverty reduction and addition in number of these institutions are the support solution which brings overall improvement in the reconciliations. The current research study investigates the impact of these MFIs towards the development of economic condition of the state. The current study aims to explore more about MFIs, economic development with the support of past counts, as well the direct and indirect benefits associated with the MFIs. Data was collected from primary and secondary sources (Mixed strategy) for creating the more rigor and objectivity under working the positivist paradigmatic approach. This study highlights the major economic problem exists in Palestine is related to poverty. Additionally, micro financing is the term associated for the development of these barriers that impacts as a hindrance for any of the economy growth level. The results of the study show that the small level micro-financing is the best resource for the economic stability as well development.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.027

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 studies0.0020.002
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.104
GPT teacher head0.340
Teacher spread0.236 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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