Impact of the Social Stock Exchange (SSE) of India for Achieving Sustainable Development Goals (SDGs)
Bibliographic record
Abstract
Purpose: Social Stock Exchange or SSE is for enterprises that work for the welfare of the society or community. These enterprises should be set up as charitable associations. SSE's objective is to provide an alternative fund-raising instrument to such organisations. To create a platform for Social Impact Investing in India, to address the funding gap and to encourage more investment in the social, environment the social stock exchange unveiled in the 2019 -20 Budget Speech by the Union Finance Minister and SEBI has formed a working group for formalizing Social Stock Exchange (SSE), Social Stock Exchange reduce the finance gap, alleviate poverty, create a better society and contribute economic development. United Nations Development Programme (UNDP) states that India needs 1 trillion per year and NITI Aayog estimate that funding equivalent to 13% of GDP is required to achieve SDG by 2030, in FY2022 Social Sector funding percentage is 9.6% of GDP. Social Stock Exchange trading platforms allow social enterprises(SE), NGOs, Civil Society organizations (CSOs), Non-Profit organizations(NPOs),and profit Enterprises (FPEs), can raise funds, through instruments like Zero coupons Zero Principal bonds(ZCZP), Donations, Social Finance, Mutual Funds, Development Impact Bonds, Social Venture Funds (SVF) both debt and equity will address the funding gap and encourage more investment in Social, Environment Cause and also encourage the SMEs start the of social Incubators/Accelerators. Brazil, South Africa, Jamaica, the UK, Canada, Portugal and Singapore have already established Social Stock Exchanges (SSE).On February 22, 2023, SEBI gave the green signal to the National Stock Exchange (NSE) to launch the Social Stock Exchange. At present, only Institutional Investors and Non-Institutional Investors are allowed to invest in the SSE. Methodology: This study is solely based on secondary data, policy documents, case studies, and the literature reviews of several scholars. The study collects information from online journals, e- papers, newspaper stories, and websites of the Government agencies for the present research article. Results & Discussion: The Main impact of this research paper A case study on 6.4 Case study of SGBS Unnati Foundation and ABCD analysis gives more insight into Social Stock Exchange (SSE) of India for Achieving Sustainable Development Goals Originality/Value: 5 S Models for Social Stock Exchange Highlights the Social Stock Exchange (SSE) of India for Achieving Sustainable Development Goals (SDGs.) Social Implication: To facilitate funding requirements through listing- Profit, Non-profit, and Social enterprises can meet the welfare of society. Type of Research: Exploratory Case Study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".