Ghosting Us All: How Hollywood Obscures the Same Environmental Issues It Foregrounds
Bibliographic record
Abstract
There is no shortage of disaster films in Hollywood. Be they natural, technologically driven, and/or the result of ideological structures that act on exploitative terms, film protagonists and societies at large engage with environmental disasters with regularity. However, if there is any change in the proliferation of such disasters and their causes, it is an increase, not a decrease or even critical discourse. Why do moviegoers experience such undeniable displays of environmental issues, yet generally are not granted access to such critical discourses by those displays? Using two blatantly similar endings to the films San Andreas and Skyscraper as a starting point, this paper examines the phenomenon of haunting to help explain how and why it can be that some of the more overt themes in Hollywood disaster films have such minimal effect upon the collective consciousness. Part theoretical considerations, part filmic narrative analysis that follows from them, the work here will bring together iterations of hauntology, Freud’s death drive, and capitalism to demonstrate shared aspects of all three that reduce the real environmental concerns at the forefront of the films’ plots to eco-ghosts. As ghosts, those concerns are present but also avoid direct discourse or resolution in virtue of haunting. Along with those of Thanos from the films of the Marvel Cinematic Universe, the experiences of the two protagonists played by Dwayne Johnson in the aforementioned films will be shown to be haunted themselves in ways that take them and the viewer close to eco issues at hand, but not in any substantive way – thus reinforcing and safeguarding the very capitalism that repeats such disasters. Article received: April 25, 2021; Article accepted: June 21, 2021; Published online: September 15, 2021; Original scholarly paper
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".