Bibliographic record
Abstract
Mapping Tokyo Olympics 3.0 is a collaborative sensory archive of demolition and displacement surrounding the three Tokyo Olympics. Understanding the Olympics as a cyclical `practice of subtraction,' where the city is not only rebuilt but unbuilt, we uncover the intertwined layers of the urban development history of these Games and the imperial (1940), high-growth (1964) and post-growth (2020/2021) periods in which they have occurred. Cancelled due to World War II, the first Tokyo Olympics were a phantom event; the second was held in the wake of massive protests against the US-Japan Security Treaty; and the third was postponed and hobbled by the global pandemic amid lingering fears caused by the Fukushima nuclear disaster. Each iteration of the Games has imposed physical effects on the urban landscape of Tokyo with the displacement of vulnerable and precarious persons as a consequence. Mapping the politics of demolition and displacement with the tools of hybrid spatial-sensory ethnography and using intermedial approaches, Mapping Tokyo Olympics 3.0 is a sensory archive of the lived experience of those displacements. Incorporating local knowledge and collaborative research-creation methodologies, we uncover layers of time, history and materiality to embrace contingencies and envision social futures. The sensory mapping archive becomes an archaeology of the future.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".