Probing Light: Projection Mapping, Architectural Surface, and the Politics of Luminous Abstraction
Bibliographic record
Abstract
Over the last decade, 3D projection mapping has flourished around the world under the auspices of corporate publicity firms, arts organizations, and urban-branding initiatives. In the popular press, this work has been hailed at once as fulfilling the ambitions of expanded cinema (freeing the moving image from the screen) and as performative architecture (liberating architecture from stasis). However, this emphasis on the freedom of the moving image, on the one hand, and on movement itself, on the other, has caused neglect toward the way that such projections interact with their architectural support. Indeed, in its short history, projection mapping has already developed favoured idioms, whose repetition across the globe draws into question its site-specificity. Whereas unapologetically commercial projects have tended toward figurative motifs, projects aspiring to the artistic have tended to systematically favour the language of abstraction. This latter group is the concern of this essay, in which, drawing on the critical framework provided by earlier inter-war debates surrounding light architecture, the author investigates the potential and limitations of such luminous abstractions in engendering new forms of spatial experience. Do these high-tech projections encourage the spectator to engage with architecture in a new way, or do they instead efface their architectural setting beneath an ornamental visual spectacle?
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.069 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".