MétaCan
Menu
Back to cohort
Record W1991252730 · doi:10.5539/gjhs.v6n1p43

Design and Baseline Findings of a Multi-site Non-randomized Evaluation of the Effect of a Health Programme on Microfinance Clients in India

2013· article· en· W1991252730 on OpenAlexvenueno aff
Somen Saha

Bibliographic record

VenueGlobal Journal of Health Science · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMicrofinance and Financial Inclusion
Canadian institutionsnot available
FundersWellcome TrustJST-Mirai ProgramPublic Health Foundation of IndiaLondon School of Hygiene and Tropical Medicine
KeywordsMicrofinanceSanitationToiletBusinessIntervention (counseling)Baseline (sea)Randomized controlled trialMedicineHealth interventionEnvironmental healthSocioeconomicsEconomic growthNursingEconomicsPolitical science

Abstract

fetched live from OpenAlex

Microfinance is the provision of financial services for the poor. Health program through microfinance has the potential to address several access barriers to health. We report the design and baseline findings of a multi-site non-randomized evaluation of the effect of a health program on the members of two microfinance organizations from Karnataka and Gujarat states of India. Villages identified for roll-out of health services with microfinance were pair-matched with microfinance only villages. A quantitative survey at inception and twelve months post health intervention compare the primary outcome (incidence of childhood diarrhea), and secondary outcome (place of last delivery, toilet at home, and out-of-pocket expenditure on treatment). At baseline, the intervention and comparison communities were similar except for out-of-pocket expenditure on health. Low reported use of toilet at home indicates the areas are heading towards a sanitation crisis. This should be an area of program priority for the microfinance organizations. While respondents primarily rely on their savings for meeting treatment expenditure, borrowing from friends, relatives, and money-lenders remains other important source of meeting treatment expenditure in the community. Programs need to prioritize steps to ensure awareness about national health insurance schemes, entitlement to increase service utilization, and developing additional health financing safety nets for financing outpatient care, that are responsible for majority of health-debt. Finally we discuss implications of such programs for national policy makers.

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)0.031
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0310.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.042
GPT teacher head0.320
Teacher spread0.278 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueGlobal Journal of Health ScienceSame topicMicrofinance and Financial InclusionFrench-language works237,207