Amazonification: A Warehouse Worker’s Manifesto
Bibliographic record
Abstract
This research-creation dissertation portfolio draws upon strategies of art-activism and uses a manifesto format to critique and subvert the exploitative labour practices of the Amazon corporation. Linked to each portfolio chapter is a custom-made, online 3D art project, or digital thinking object, in the shape of a globe that was created using the modelling platform SketchFab. Located on the Amazon “globe,” signifying the global nature of Amazon’s impact, are five different symbolic objects that function as entry points to the five manifesto essays of this dissertation, which include references and links to documentation of my anti-Amazon art practice. The introduction, “Amazonification: A Warehouse Worker’s Manifesto,” is represented through a palm tree, whose many leaves denote a network where shipping infrastructure is repurposed into sites for community-oriented acts of care. Chapter one, “Define Amazon” is symbolized by Danbo, Amazon’s “adorable” cardboard mascot whose “cuteness” obscures the violence of Amazon’s labour practices. In chapter two, “Seeing Orange,” symbolized through an orange ball, I make connections between Amazon’s orange mascot, Peccy, and prison jumpsuits, carcerality, and labour exploitation, and reclaim the colour as a colour of healing by invoking Orange Shirt Day in Canada, Buddhist robes, marigolds, and mehndi. In the third art manifesto chapter, “Peccy: the Fiction of a ‘Happy’ Worker,” I position the mascot’s eyes as the corporation’s surveillance infrastructure, and the mascot’s (non-gendered and non-raced) “blob” body as the dehumanization of Amazon’s predominantly racialized workers’ bodies. In the final manifesto essay, “Ongoing Struggle: Unionizing Environments in Chicago, Bessemer, and Minneapolis” the Amazon Workers’ International logo symbolizes the labour activism of Chicago’s DCH1, Bessemer’s BHM1, and Minneapolis’ MSP1 warehouse workers’ challenges for unionization between 2018 to 2021, activities crucial to resisting labour exploitation and building community. This dissertation does not just critique Amazon; it prompts viewers to begin to envision a different future. By foregrounding labour unions and the experiences of poor, working-class, Black and brown Amazon warehouse workers, I call for the fostering of a compassionate “network of care.” This portfolio dissertation is a call to hold a multiplicity of pathways toward this future self-determined by the people whose labour Amazon exploits: pathways that range from advocating for better workplace conditions, to shrinking the corporation, to divesting, to dismantling and abolishing the corporation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".