“Tax Amazon, Not Working People”: Left Populism and Labor Organizing in Seattle
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Bibliographic record
Abstract
Abstract This paper examines the role of labor and community left populist organizing in the Tax Amazon campaign based in Seattle, WA, USA. As a case study within a larger project that examines manifestations of both right-wing and left-wing populism in urban spaces, the paper presents a lens through which urban populism may be examined in relation to new forms of labor organizing, with a specific focus on the dynamics of left populist resistance. The Tax Amazon campaign is situated within a longer trajectory of contemporary left populist organizing in Seattle. Emerging from a previous campaign that resulted in Seattle City Council instituting a $15 minimum wage, the Tax Amazon campaign brought together labor and community organizations to pressure Seattle City Council to introduce a corporate tax to generate funding for affordable housing initiatives. The campaign was met with resistance from the local business community, as well as some local trade unions. Being a leading corporate figure in this opposition, Amazon emerged as a key target of the left populist campaign. Through this study, we ask, what role did labor-community coalitions play in shaping the emergence of a broader left populist politics at the municipal scale in Seattle? Building from the experience of the Tax Amazon campaign, the paper reflects on the dynamics of resistance to corporate power through labor- and community-based left populist organizing. Reflecting a shift in U.S. politics at the municipal scale, Seattle offers a key case through which to assess whether and how urban populism may give rise to new forms of labor organizing. The paper also considers the ways in which the simultaneity of the Tax Amazon campaign and the Movement for Black Lives to ‘Defund the Police’ expanded the scope of political demands in the context of Seattle’s racialized urban precarity. In its conclusion, the paper draws from the analysis to reflect on both the broader prospects and limitations of left populist organising.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it