Bibliographic record
Abstract
Since its founding in 2008, W.A.G.E. (Working Artists and the Greater Economy) has worked to reform the economic habits of US art institutions and of the artists upon whose cultural work these institutions are dependent. Inside a decade, W.A.G.E. went from a small grassroots collective to an internationally recognized, yet lean, organization, which not only advocates for labour standards in the nonprofit art sector, but also develops practical tools to begin the work of doing better by equality in the art world. This chapter positions W.A.G.E. as an example of what Immanuel Ness terms “new forms of worker organization.” Informed by W.A.G.E.-authored texts, media coverage of W.A.G.E., and interviews with the group’s core organizer and programmer, the chapter surveys W.A.G.E.’s strategies for organizing “dark matter,” a concept that Gregory Sholette has repurposed from physics as a metaphor for the majority of artists and activities that populate the art world and uphold and subsidize its most visible and commercially successful figures. W.A.G.E. is explored in five registers: its practice of parrhesia, algorithm of fairness, strategy of certification, post-horizontalist form of organization, and platformization of labour politics. While W.A.G.E. has been tackling dilemmas specific to the nonprofit arts, its strategies hold wider relevance to confronting the challenge of organizing workers who are outside of an employment relationship, who lack access to unions, and for whom the opportunity to be self-expressive or the promise of exposure may be regarded as compensation enough.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.037 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".