Bibliographic record
Abstract
Purpose The purpose of this paper is to take a dispassionate look at the performance of the Indian economy in the light of its recent growth rate acceleration. After 2000, it recorded several years of vertiginous gross domestic product (GDP) growth rate, which made some think that the growth trajectory of the economy is shifting upwards. A careful data analysis reveals that growth optimism is misplaced. There are several areas of the economy that have suffered from limitations and long‐term neglect of the policymakers. The paper clearly and concisely enumerates them. What is disconcerting is that these long‐term weaknesses were not addressed and are still persisting. Sluggish and tardy reform implementation is one of the serious bottlenecks. In addition, in 2008, myriads of domestic and global factors coalesced to drive GDP growth rate sharply down. Design/methodology/approach This paper carefully analyzes the current economic data to examine whether the recent GDP growth rate achievement can be sustained. Findings The principal inference of this paper is that the growth spurt of the Indian economy is unsustainable. Although the economy has a great deal of potential, expectations of a China‐like growth in the foreseeable future are totally unrealistic. Originality/value The paper proposes a pragmatic plan to break out of this economic quagmire. The value of the paper lies in its succinct and objective analysis of the Indian economic performance, its recent past and the immediate future. Without overlooking its recent achievements, the paper provides a credible vision of the future performance of the Indian economy.
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 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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".