FILMS OF ESCHATOLOGICAL CATASTROPHISM AS CULTURAL ARTIFACTS OF THEIR TIME: CONSIDERATION IN HISTORICAL DYNAMICS
Bibliographic record
Abstract
This article is devoted to the identification and research on films of “eschatological catastrophism”, their evolution and features. The concepts of “catastrophism” and “eschatology” and their relationship are indicated, and on this basis the author's concept of “eschatological catastrophism” in cinema and its attributive signs are revealed. The methodology used in this article includes the analysis and synthesis of films, considering the historical dynamics and their relationship with the socio-cultural context of the era. The study covers films produced in the USA, France, Italy, China, and Canada and other countries. The general trends in the development of eschatological catastrophism films, the factors that determined the rise of these films, are reflected. This research explains the reasons behind the popularity of catastrophe films in a particular period, and using the method of sociocultural observation, the philosophy of films and the dynamics of changes in the semantic context of eschatological catastrophism in the period from 1910-2020 are tracked. The possible reasons for the demand for the secular apocalypse films at the intersection of the XX-XXI centuries are discussed.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".