Constructing and contesting the Olympics online: The internet, Rio 2016 and the politics of Brazilian development
Bibliographic record
Abstract
The awarding of the 2016 Summer Olympics to the city of Rio de Janeiro, Brazil continues the trend of international sports mega-events being hosted in the global South and constructed and promoted as part of long-term development plans and policies. Rio 2016 also connects with the International Olympic Committee’s (IOC) current commitment to international development and global humanitarianism. In this paper, we examine the proliferation of this agenda through official online Olympic communication and compare it against critical perspectives from activist bloggers concerned with development issues specific to Rio 2016. The results support the notions that the internet can be used both to serve and challenge processes of capitalist accumulation and that political debates and contestations, such as those regarding development policy, are increasingly ‘amplified’ online. We argue, therefore, that while the IOC and Olympic stakeholders use the internet in support of neoliberal and modernist notions of development, online communications also offer important avenues for disseminating current critiques of, and resistance to, Olympic hosting.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".