Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this article is (1) to posit a conceptual model for the way ideas, conceptions, or feelings are represented or ‘figured’ in memory with the help of the imagination, and (2) to use this model to begin to outline what I believe constitutes part of our culture’s ‘memory-image’ of the serial killer in both fact and fiction. Human memory is not simply a passive storehouse of information. It is an active process whereby relations are created by way of the imagination. The ‘memory image’ is connected to what we wish to remember, but also to other images stored in memory, and inscribes itself in a vast ‘figural network’. I show how a given metaphor – ‘capitalism as cannibalism’ – can find its way in a given figural network, that of our memory-image of the serial killer. I investigate the rhetorical network that surrounds cannibalism and examine how this network offers our imagination a topos for our memory-image of the serial killer. Finally, I look at two films that activate this topos in their representation of serial killing, even though they avoid any direct thematization of it. The absence of any act of cannibalism in these films makes its ‘presence’ in our experience of them all the more compelling.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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 it