Bibliographic record
Abstract
Nothing is as purely imaginary as the digital archive. Like a brilliant specter from the vast recesses of the cultural universe, the digital archive sweeps through the night skies of the mind, turning time’s past into real-time, lighting up spatial horizons with light-space, folding the historical past into the projected future, breaking down fixed boundaries, always following the unpredictable pathways of the awaiting imagination. Never really interested in truth-telling, nor particularly loyal to the concept of bunker archeology, the digital archive is that rarest of cultural phenomenon: a code matrix tracing an uncertain arc across the human condition, projecting retrieved memories into the present, here confronting the solid matter of reality with imaginary reconstructions of the past, there gathering speed as the code matrix is propelled forward by the gravitational force-fields of the surrounding planets of society, economy, and culture, always becoming in the process something more intense, more vivid, more purely imaginary.
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 | 0.024 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.031 | 0.026 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.151 | 0.069 |
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".