MétaCan
Menu
Back to cohort
Record W2519218539 · doi:10.5539/ibr.v9n10p162

Gender Based Utilization of Microfinance: An Empirical Evidence from District Quetta, Pakistan

2016· article· en· W2519218539 on OpenAlexvenueno aff
Abdul Naeem, Sana ur Rehman

Bibliographic record

VenueInternational Business Research · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsMicrofinanceNet profitRevenueNet incomeProfit (economics)Profit marginBusinessImpact evaluationSocioeconomicsDemographic economicsFemale entrepreneursEconomicsEconomic growthMarketingEntrepreneurshipFinanceMathematics

Abstract

fetched live from OpenAlex

<p class="1main-text">This study examines the impact of microfinance on gender based income generating activities of the Khushhalli Bank Ltd client’s in urban zone of district Quetta during year 2011. The Primary data was collected through structured questionnaire from 80 clients (60 beneficiaries and 20 non-beneficiaries) by adopting cross sectional experimental design.</p><p class="1main-text">In order to analyze the collected data the t-tests were applied. The results show that the microfinance has a positive impact on both male as well female beneficiaries as compare to non-beneficiaries in term of increase in business performance. It has non-significant impact on average sale revenue of both male as well as female micro-entrepreneurs. Whereas it has a significant impact on average net profit, average fixed assets as well as average net worth of the male but having non-significant impact on female established micro-entrepreneurs. Comparison of gender based business performance reveals that the microenterprises operated by male are able to generate better revenue and net income performance also the same results are obtained in case of enhancement in fixed assets as well as net worth. So we may confidently say that male clients are able in utilizing the microfinance services more effectively as compared to female.</p>

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.318
GPT teacher head0.429
Teacher spread0.111 · 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.

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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Business ResearchSame topicMicrofinance and Financial InclusionFrench-language works237,207