The Political Economic Roots of Hollywood Strikes, 1950-2023
Bibliographic record
Abstract
This paper investigates the timing of labour strikes in Hollywood. The occurrence of strikes, such as the WGA and SAG-AFTRA strikes in 2023, can make sense when we have the hindsight to piece together the historical details of what created rifts between labour and management. But why do strikes in Hollywood occur when they do? Are there periods of time when it is more likely that contract negotiations will break down and unions in Hollywood will go on strike? This paper uses multiple sources of empirical data to analyse the historical trends of strikes in Hollywood between 1950 and 2023. Strikes in Hollywood - particularly by the WGA and SAG-AFTRA - have common political economic roots. They tend to occur when the profits of major Hollywood studios are in a type of danger zone: when the differential profits of Hollywood are stagnating or declining. Differential profit is a relative measure of performance. Differential profit can be found in any situation where a firm or set of firms holds a better stream of income than what others hold. For example, differential gains still occur when a firm loses profit at a slower rate than others. In the case of the Hollywood studios, differential profit is measured against Dominant Capital, which is our proxy for the S&P 500. The paper argues that danger zones of differential accumulation hurt Hollywood labour because Hollywood's major studios often rely on stagflation to differentially profit. As a combination of unemployment and inflation, stagflation is antagonistic to union demands for increased employment, job security, or higher wages. In Hollywood, strikes tend to occur during periods when film production is stagnating. The longest absence of strikes was from 1990 to 2000, when Hollywood reversed its stagflation strategy and released films at a level that was not seen in decades. Stagflation also has an influence on the management-artist hierarchy in Hollywood. While standard artist contracts in Hollywood construct a hierarchical structure that effectively prevents artists from exercising moral rights in opposition to aesthetic changes by management, increases of stagflation in Hollywood increase the employment size of management, both absolutely and relative to the collective employment size of actors, directors, producers, and writers.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".