National innovation system of India: genesis and key performance indicators
Bibliographic record
Abstract
The article discusses the formation of the India’s national innovation system (NIS), which passes through the phases of protectionism, liberalism and duality. Special attention is paid to the peculiarities of the India’s innovation system based on efficiency indicators, such as gross domestic expenditures on research and development, exports of high-tech products, as well as foreign direct investment in high technology sector. The paper notes that India is one of the most attractive countries for investing in the innovation sector. The author also highlights the negative aspects of NIS development in India, such as imbalances in income and wages, low literacy and high levels of poverty, uneven inflow of foreign investment in different regions, lack of innovation culture in manufactured products, etc. The article especially notes that India after the start of the process of economic liberalization has grown economically in terms of GDP, exports, employment, investment, the inflow of foreign technology and investment, the ICT industry, and the internationalization of investment in research and development sphere.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".