Bibliographic record
Abstract
In Darren Aronofsky’s 2000 film, Requiem for a Dream, based on Hubert Selby Jr.’s 1978 novel, he depicts extreme close-up images of heroin as it cooks, boils, enters a vein, and then passes into the body at the cellular level. The cells sizzle as heroin numbs them. The close-ups and sizzling sounds repeat themselves more and more frequently as our four main characters disintegrate through the process of becoming junkies. These images and others provide vivid, horrific, and exquisite visual renderings of the addiction process, while simultaneously providing stark evidence of heroin’s take-over of the body, mind, and ethical capabilities. The images of heroin’s allencompassing control of the body at its foundational level do not glorify heroin’s power in Aronofsky’s film; these images serve as documents of pure horror. The degradation is devastating, thorough, real, and scarring. Aronofsky describes his film as a monster movie, a modern horror film. And, it is not the type of film in which redemption occurs. The stark and individual solitude of each character at the end of the film cannot be easily penetrated by sobriety or love anytime in the foreseeable future.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".