Dying to Work: Oʻahu Hotel Workers’ Efforts at Well‐being in the Face of Autoimmune Capitalism<sup>1</sup>
Bibliographic record
Abstract
Abstract The settler colonial state of Hawaii has fostered tourism as its primary economic activity, despite its being only one‐fifth to a quarter share of the economy. As a result, the push to reopen tourism in the face of COVID‐19 pandemic conditions, which ground the industry to a near halt in 2020, has been acute. Based on our long‐term involvement with UNITE HERE! Local 5 and our participation‐observation of union members’ activities since May 2020, we examine worker‐led safety protocols and practices to promote public health in the face of state and industry actors’ conscious exclusion of their expert knowledge in order to revive tourism. This exclusion put barriers in the way of hotel workers returning safely to their jobs and ultimately cost lives. We call this self‐destructive urge “autoimmune capitalism,” an autophagic assemblage that consumes the mostly immigrant and Indigenous workers integral to the operation of tourism in the state. As tourism returns, hotel workers continue to organize for life‐affirming practices even as their radical care to ensure community well‐being gets absorbed as an invisible and uncompensated component of the pandemic service economy.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".