Published or Perished: thoughts on the publication of mediocrity
Bibliographic record
Abstract
Some of these points have already been touched upon in Discoverability of published objects(2) but to summarize: • Justification for publishing such materials: it provides a footing or foundation upon which others can build. Or avoid the mistakes that we made. • Also better than sitting hidden on a hard drive (which will eventually die or become obsolete because the OS cannot be upgraded any more i.e. Perished) - see ‘Archiving the data’ below. For those projects that did not come to fruition, this is the equivalent of publishing negative results (which many editors call for but few will actually do).(3–6) We are aiming for a different audience with this kind of publication. Back when scholars would patiently wander through the stacks, you would not want to waste their time with cluttering up those stacks with such mediocre material. But things have changed: our browsing/foraging behaviors have changed.
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 | 0.040 | 0.199 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.028 | 0.037 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.033 | 0.009 |
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".