National innovation system of India: genesis and key performance indicators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it