Bibliographic record
Abstract
In this article, the author argues how the conceptual curatorial work of Lucy Lippard imbued similar qualities to those that are embodied in the curatorial work of the ‘aesthetics of the undeliverable’. The aesthetics of the undeliverable is a new genre of disability curating that centers the realities of disability and access within curatorial and artistic practice, alongside exhibition design. The line that runs through both styles of curatorial practice, that is, Lippard’s work, and the aesthetics of the undeliverable, is political intent, where the behind-the-scenes labor of the curator is revealed. Specifically, in Lippard’s projects, errors, gaps, and professional time-frames were revealed, whilst the aesthetics of the undeliverable points out inequities towards disabled artists and audiences, yet insisting on time-lines that defy normative frameworks. The author examines these generative comparisons through Lippard’s ‘numbers’ exhibitions curated in the 1960s–1970s, alongside a case study of the exhibition, Undeliverable, curated by artist Carmen Papalia, which was held at Tangled Art + Disability Gallery in Toronto, followed by the Robert McLaughlin Gallery in Oshawa, Ontario in 2021. In doing this, she aims to show how the aesthetics of the undeliverable is a form of institutional critique within disability arts and culture that has its roots in the proponents of conceptual art of the 1960s and Lippard, to which crip curating is aligned through its oppositional handling of curatorial norms. This dovetails powerfully with a call by Disability Studies scholars to move towards crip methodology, and this article will show how crip curation and the aesthetics of the undeliverable heeds this call.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.016 | 0.059 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".