Ageing Masculinities and “Muscle work” in Hollywood Action Film
Bibliographic record
Abstract
In August 2010, the sixty-four-year-old Hollywood icon Sylvester Stallone premiered his latest project The Expendables, an action-adventure film starring a pantheon of “tough guys” from both past and present: Sylvester Stallone, Arnold Schwarzenegger, Dolph Lundgren, and Bruce Willis. To understand the resurrection of this vintage Hollywood cast, we take up the title theme of “expendability” within the climate of the economic recession of 2008 and map its representation of masculinity, physical labor, and ageing. We do this by looking at The Expendables as essentially a labor text. In doing so, we find a smorgasbord of working bodies and types of physical labor that reveal multiple intersections among discourses of masculinity, class, ageing, and race that simultaneously reflect the divisions of (physical) labor in the industries in which the stars work—Hollywood film and professional sports.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".