Advancing Sustainable Development Goals (SDGs): An Analysis of How Non- Financial Services of Microfinance Insitutions Facilitate Human Capital Development of Clients in Ghana
Bibliographic record
Abstract
In 2015, the United Nations General Assembly adopted the 2030 Agenda for Sustainable Development, together with seventeen goals that are collectively called the Sustainable Development Goals (SDGs). This study examined the effects of non-financial microfinance services on human capital development of clients and discusses its implications on the achievement of the Sustainable Development Goals. The case is drawn from Sinapi Aba Trust (SAT), which is a microfinance institution of Ghana. Primary data were collected from 361 clients in seven districts of the Ashanti Region, Ghana. The results of the ordinary least square (OLS) regression showed that non-financial services offered by SAT had positive significance on human capital development of the clients. This finding shows how additional services from microfinance institution could help clients to maximise the value of loans offered to support income-generating economic activities. For clients, the study also draws attention to the need for them to take non-financial services offered by microfinance institutions seriously to improve on their own human capital development in the context of the SDGs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".