A Study on the Scope of Implementation of Social Stock Exchange in India
Bibliographic record
Abstract
Social Stock Exchange provides access to dedicated investors and businesses seeking to achieve a positive social and environmental impact through their activities. The aim of a social stock exchange is to act as a platform to bring social organizations and investors together whose missions and interests align with each other. Social stock exchanges are already established and functioning in a handful of countries including United Kingdom, Canada, South Africa, and Singapore. As far as India is concerned, SEBI has taken quick action to respond to the implementation of social stock exchange proposed in the Union Budget 2019, by forming a working group to examine and make recommendations for the same. The main objectives of this research paper were to analyse the working of SSEs in different countries using a descriptive study method. On understanding the working of SSEs around the globe, we have suggested certain features that can be implemented in the Indian Social Stock Exchange. We have also brought out the differences in the terms closely related to Social Stock Exchange like- Impact Investing (II), Socially Responsible Investing (SRI), Environmental, Social and Governance (ESG), and Thematic Investing (T.I.).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".