Corporate Social Responsibility Funding and Its Impact on India’s Sustainable Development: Using the Poverty Score as a Moderator
Bibliographic record
Abstract
This study investigates the impact of corporate social responsibility (CSR) funding in the education sector and the environment and how it affects India’s sustainable development. This study was conducted using secondary data and the data were collected from 28 Indian states and three union territories for the four fiscal years 2018 to 2021. This study examines the hypothesis using the generalized method of moments (GMM). As a result, it is found that overall CSR funding positively contributes to India’s sustainable development. Additionally, this study finds that CSR funding in education and the environment supports India’s sustainable development. It is also observed that, under the interaction effect of poverty (poverty score), CSR funding (total) and CSR funding on education positively affect sustainable growth. However, CSR funding for environmental activities does not significantly influence India’s FD under the moderation of poverty score. These factors are essential for India’s sustainable development and poverty reduction. Investing CSR funds in rural development, education, the environment, health, and other areas supporting India’s sustainable development leads to impressive economic growth and reduces poverty. Hence, it is attributed that CSR funding plays a vital role in India’s sustainable development. Future research can be carried out on CSR policies and funding using different variables and periods.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".