`The photographer of modern life': Jeff Wall's photographic materialism
Bibliographic record
Abstract
In this article I explore the work of the Canadian artist Jeff Wall whose innovative photographic methods have come to challenge the traditional pictorial protocols linking the photographic image with its referent. Wall uses large format images enlarged on transparent synthetic film and mounted in lightboxes as a medium to explore various aspects of everyday life in capitalism. My main purpose is to reflect on the historical specificity and ontological complexity of Wall's turn to deep pictorial illusion. To do so, I argue that Wall's back-lit transparencies point to a re-materializing of longstanding historical connections between pictorial representation and art's social function as a relation of radical critique. Such traffickings between the `visual' and the `material' have increasingly become the source of debate with cultural geography and cultural theory more generally, and this article draws particular attention to the various patternings of landscape, spectacle, and everyday life that have come to characterize Wall's formal photographic repertoire. As I hope to show, not only does Wall's work give new credence to the notion of `representation' but it also testifies to a revivified engagement with the materialities of picture-making. Indeed, what is ultimately at stake in Wall's work is an emphasis on presencing the material possibilities that are, in his view, inescapably inscribed within the practice of photography.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.052 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 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".