Invited Guest Editorial: Quaint Memories of Puzzling Through Mysteries
Bibliographic record
Abstract
The incompleteness of meaning and the finitude of understanding suggest that the subject matters (die Sache) of understanding are mysteries rather than problems. Mysteries are not subject to the methodological solutions problems are. A problem denotes a difficulty demanding a solution. Mysteries however can only be understood more deeply. They are not to be explained away but are to be discerned as an ever-present limit to our understanding. They invoke an apprehension of a radical limitlessness (Davey, 2006, p. 29).I had the good fortune of supervising John’s thesis—a mysterious venture to be sure, because when we started, neither the path nor the destination were clear. In this editiorial I preface John's latest installment of his serialization of The Case of the Disappearing/Appearing Slow Learner: An Interpretive Mystery. Part Four: Quaint Notions of Justice.
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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".