Bibliographic record
Abstract
between digital policies and objective of banking, 71-73 Banswara Village, case study of, 27 Behavioural social capital, 27 Bharat Bill Payment system, 108 BHIM (mobile application-based fund transfer system), 93-94, 96-97, 108 BOLT, 48 Bombay Plan (1944), 2-3 Bombay stock exchange digitisation of, 48 index, 48 Borrowers, 123 Borrowings from self-help groups, 132-133 Bridging capital, 34 British rule, 9 Bruntland commission, The (1987), 154 Bulk Payment system, 101-102 Bureau of Police Research and Development (BPR&D), 157 Business decision, issue with, 165-166 Business email impostors, 141 Call Money, 55 Canadian International Development Agency (CIDA), 25 Capacity building importance of, 19 initiatives, 5-7 Capital formation, 50 metaphor of, 30-31 Cash, 94 transfers, 162-163 Cash Benefit scheme, 162-163 Cash-in cash-out (CICO), 114 Cashless economy, 96-97 challenges to, 114-116 digital capital, 115-116 of India, 93-94 social perspective, 93-94 Cashless financial systems benefits of financial inclusion and digitization, 116-117 cashless economy of India, 93-94 challenges to cashless economy, 114-116 digital money, 96-97 e-Governance in India, 98-99 financial inclusion and consumer data protection, 114 Fintech Companies, 113-114 Indian stack, 101-102 nine pillars of Digital India, 99-101 Payment Banks in India, 112-113 policy ecosystem, 108 reforming e-government through technology, 102-108 transforming India's digital payment landscape, 108-112 vision of digital India, 97-98 Casteism, 7-8 Central Bank of India, The, 60, 114 Central Government Health Scheme (CGHS), 156 Central sector schemes, 127-128 Centre for Monitoring Indian Economy (CMIE), 130 Centre for Water Resources Development and Management (CWRDM), 153-154 Certificate of deposits, 55, 65, 143-144, 184, 187 Choonthumani (earrings of Paniya tribe), 33-34 Circular flow of money in economy, 50-51 Climate Change, 152-154 initiatives for, 155 Climate refugees, 153-154 Cluster approach, 42 Cognitive social capital, 27 Collateral-free lending system, 132-133
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.
How this classification was reachedexpand
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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.029 | 0.709 |
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; both teacher heads agree on what is shown here.
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".