Bibliographic record
Abstract
This case study of a union campaign to organize personal trainers and fitness instructors at GoodLife Fitness, the world’s fourth-largest fitness chain, is used to highlight the challenges and possibilities of organizing precarious workers in the multi-billion-dollar fitness industry. Drawing on the broader literature on union organizing and strategic corporate campaigns, primary documents related to the organizing drive, media coverage of the campaign, and in-depth interviews with union officials and fitness workers, the case study reveals how the workers were successfully, yet unconventionally, able to leverage institutional, symbolic, and associational power to build union muscle in an industry that is virtually union-free.
 
 Cette étude de cas d’une campagne syndicale visant à organiser des entraîneurs personnels et des instructeurs de condition physique chez GoodLife Fitness, la quatrième chaîne mondiale de condition physique, est utilisée pour mettre en évidence les défis et les possibilités d’organisation des travailleurs précaires dans l’industrie de la condition physique de plusieurs milliards de dollars. S’appuyant sur la littérature plus vaste sur les campagnes syndicales et stratégiques d’entreprise, sur les principaux documents relatifs à la campagne de syndicalisation, sur la couverture médiatique de la campagne et sur des entretiens approfondis avec des responsables syndicaux et des professionnels de la condition physique, l’étude de cas révèle comment les travailleurs ont réussi, de manière non conventionnelle, à tirer parti du pouvoir institutionnel, symbolique et associatif pour renforcer le pouvoir syndical dans une industrie pratiquement sans syndicat.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".