Bibliographic record
Abstract
This paper examines the competing ‘languages’ of line in Julie Mehretu’s series, Grey Area (2007–9) and elaborates on the implications these lines have for theories of space, bodies and, in particular, the relationship between the two. Grey Area explores what Mehretu describes as a grey and in-between space. The series is composed of seven large abstract canvases covered in an assortment of gestural tracings and neatly traced rational lines (e.g. architectural lines). The juxtaposition of these competing linely narratives not only creates a grey space visually, but compels viewers to stretch their bodies across the canvases and between the lined layers thus, facilitating a brief inhabitance of grey space. Building from this analysis, the paper reflects on the relevance of the lines and the stretching they elicit for examining the complexities of contemporary modes of inhabitation that often extend across multiple geographical sites and temporal modes. Thus, engaging with Mehretu’s lined abstractions draws attention to the importance of space in the production of bodily boundaries, what I call geographical and temporal bodily outlines. In addition to contributing to body-space theories, the paper also demonstrates the valuable insights gained by attending to the unique social-aesthetic analyses of visual art and artists.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".