“If the art ends up being pretty, making it here won’t be”: Examining Precarity, Neoliberalism, and Artists’ Labour on CBC’s <i>Crash Gallery</i>
Bibliographic record
Abstract
Background: In 2015, the Canadian Broadcasting Company launched Crash Gallery, a reality TV series in which artists from across Canada compete in playful challenges. Analysis: This article analyzes the impact of neoliberal priorities on federal arts funding and CBC television programming. It considers the imprint of neoliberalism on depictions of artists and artistic labour on Crash Gallery via themes of: individual competition and meritocracy; temporary and precarious work; flexibility and non-routine ways of working; compulsory sociality and emotional labour; and hazardous working conditions. Conclusions and implications: Crash Gallery’s depictions of artists as flexible, passionate, and willing to work under hazardous circumstances naturalizes and valorizes neoliberal working conditions for artists in Canada.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.031 | 0.047 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".