Bibliographic record
Abstract
It seems fitting to explore an alternative form of introduction to an issue that promises other interior worlds. It also seems fitting to take up the opportunity to experiment with digital interfaces, word processing software and audio-visual media to exploit the static state of the page in favour of the spatial, the temporal and the audible. “introducing, inducing” is a product of fabulation, and evidence of the journal’s commitment to push the boundaries of the multiple practices it reflects and the modes of making creative practice research public. The cover image created by Sophie Forsythe forms the first layer — a doorway, a threshold — that articulates a stretched, warped, morphed and fragmented world of many dimensions, unfettered by the tired binary of inside and outside. Its textures, surfaces and ethereal colours wrap space akin to spring pea tendrils, reaching towards luminosity with heliotropic determinism, and pushing through the flat page like new potatoes. References to each article contained in this journal issue lurk amongst this visual dissonance, slipping in between its layers, like English Numbers Stations, giving themselves up to forces other than gravity and voices other than human.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.046 | 0.018 |
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".