Bibliographic record
Abstract
Sports mega-events tend to follow a top-down, increasingly neoliberal, developmental logic that reflects the aspirations and material interests of their host countries’ elites. The 2010 Commonwealth Games (CWG), held in Delhi, India, falls within this pattern. It also provides valuable insight into the country’s larger development trajectory. I locate the roots of the CWG’s troubling effects, such as slum demolitions and securitisation of the city, not within neoliberalism per se, but within a paradigm of ‘development’ that equates ‘progress’ primarily with catching up with the West. I emphasise the striking similarities between the CWG’s impact on Delhi, and that of the 1982 Asian Games, which India hosted while it was still following a state-interventionist development model. Much like the organizers of the CWG, the organisers of the Asian Games tried to convert Delhi into a ‘modern’ city cleansed of shanty towns and street vendors. Although this effort was ultimately unsuccessful, it produced many adverse consequences for the city’s marginal populations. When compared, the legacies of the CWG and Asian Games indicate that it is the larger paradigm of development at work in India that ought to be questioned, not only how it is actualised through state-interventionist or free-market (neoliberal) policy.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".