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Record W7134170375 · doi:10.5281/zenodo.18911189

Female Entrepreneurs' Adoption of Mobile Banking Services in Urban Nairobi Markets,

2010· article· en· W7134170375 on OpenAlexaff
Mwangi Kahora Gitonga, Omondi Muriungi, Kinyanjui Wambui, Chiraimba Ochieng

Bibliographic record

VenueOpen MIND · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsMobile bankingFinancial servicesFinancial literacyInvestment (military)Mobile paymentQualitative researchFinancial inclusionMobile deviceDeveloping country

Abstract

fetched live from OpenAlex

Female entrepreneurs in urban Nairobi markets have shown limited adoption of mobile banking services despite recent advancements in technology. A mixed-methods approach combining quantitative surveys with qualitative interviews was employed to gather data from 100 randomly selected female entrepreneurs within Nairobi's urban markets. Mobile banking usage among female entrepreneurs varied significantly, with approximately 45% using mobile services for transactions and payments. Financial literacy and digital comfort were key determinants of adoption rates. Despite the potential benefits of mobile banking for women's businesses, limited awareness and financial literacy remain significant barriers to its widespread adoption. Investment in targeted education programmes aimed at improving female entrepreneurs' access to and understanding of mobile banking services is recommended. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.240
Teacher spread0.222 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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