Financial Capability of Educated Middle Class in India — A Study
Bibliographic record
Abstract
Financial capability is defined as having the knowledge, understanding, skills, motivation and confidence to take financial decisions which are appropriate to one's personal circumstances. Financial capability can only lead to financial well being. A person's financial capability is best demonstrated by his/her behaviour. Someone can be financially literate without being financially capable. Both developed and developing countries are making continuous efforts to enhance financial capability of their citizens. It is widely believed that strengthening of financial capability would play an important role in increasing levels of financial inclusion, improving efficiency and stability of financial markets, and enhancing welfare outcomes for consumers. US, UK, Canada, Australia, New Zealand, Brazil, Fiji, Eastern Caribbean Currency Union, Ghana, Hungary, Ireland, Malaysia, Singapore, South Africa, Tanzania, Trinidad & Tobago and Kenya have already initiated steps to conduct national level studies on financial capability to identify capability deficits of various segments of their population and vulnerability of selected groups within the population in order to develop comprehensive national strategies for improvement of financial capability of their citizens. India has so far not done any noticeable efforts in this direction. In this paper, the researcher has attempted for the first time to test the financial capability of Indian educated middle class. It has been suggested that the Government of India should initiate steps for undertaking a national level financial capability study of Indian citizens, with special emphasis on financial capability of socio-economically vulnerable groups and initiate appropriate policy interventions to strengthen this capability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".