Bibliographic record
Abstract
When we return to certain memories, whether they be stored for us as images in the mind, or as binary data, we imagine these figments to be essentially siteless, floating. We think of "the cloud" as existing immanently, all around us, hanging in the air between screens. And it is. But it is also anchored to real, monumental amounts of physical space. It is not just everywhere, it is somewhere on Earth, sitting on millions of square feet of land, ready to be called up in front of any eye with the right keywords. Paper Monuments examines the substance of memory, our relationship to the unseen, and the narrative scaffolding we build around these figments. Analyzing the ever-evolving technologies of memory, this paper reflects on the unending loop between seeing, remembering, and knowing, and the funciton of images within this cycle. It proposes that images are not pointing us toward the past histories or narratives to which they appear to be anchoreed, but towards a future past—a past which has not yet come to be, a perfect past, where we had it all.
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 | 0.000 | 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 | 0.000 | 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) | 0.001 | 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 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".