‘Celebrate humanity’ or ‘consumers?’: A critical evaluation of a brand in motion
Bibliographic record
Abstract
The Olympics is a global event that acts as a carrier of cultural meanings and identities that are available to international audiences and markets. Our wider project examining the Athens Olympic Games seeks to investigate how such meanings are re-represented, distributed, and marketed by the media-sport complex. Here, we investigate how the initial formulation, development and use of the ‘Celebrate Humanity’ programme was framed by the IOC marketing department as a way both to deflect criticism of the IOC and as one means by which to provide ‘added-value’ to TOP sponsors. Attention is given to two main sources: IOC documents and interviews with personnel from TOP sponsors and representatives from their advertising agencies. Our conclusion is that this programme, and the wider Olympic movement, is characterized by a basic contradiction between the ideals of ‘Olympism’ and the realities of the modern Olympics in practice. The ‘message’ becomes embedded in a broader process of commerce whereby the media/marketing/advertising/corporate nexus is concerned less with the values underpinning Olympism per se and more with how such values can help build markets, construct and enhance brand awareness and create ‘glocal’ consumers/identities. ‘Celebrate Humanity’ is no exception.
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 | 0.039 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.024 | 0.081 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".