Olympic Aspirations or Developmental Illusions? A Critical Analysis of India’s 2036 Olympic Goals and Mega Sports Events
Bibliographic record
Abstract
India’s bid to host the 2036 Summer Olympics, with Ahmedabad as the proposed host city, reflects both national pride and a strategic attempt to project soft power. Anchored in the ambitious Sardar Vallabhbhai Patel Sports Enclave, the initiative highlights India’s aspirations to join the ranks of Olympic host nations. This remarkable ambition raises concerns about feasibility, equity, and sustainability. Through a qualitative, comparative case analysis of past hosts—Canada (1976), Greece (2004), Brazil (2016), and Japan (2020) the present study examines India’s sports infrastructure, governance readiness, and socio-economic implications. Now the question is whether mega-events can drive inclusive development or whether they risk financial excess, urban inequality, and social displacement. The paper argues that while the Olympics could enhance India’s global image, they also carry significant risks. For the bid to succeed, India must balance international ambition with grassroots sports development, sustainable planning, and long-term legacy creation.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".