Editorial The Pleasures of Silence
Bibliographic record
Abstract
I arrived early at Melriches Café after spending the morning at the University, so I was able to grab a good table with a view of the street. The week before, Gary Genosko had e-mailed me to arrange for us to meet up on his way home to Thunder Bay from Victoria. As I sipped my latte, I recalled that this would be the first time we’d seen each other since February 2000 when he invited me to give a talk to his department at Lakehead (‘Weber’s Tolstoyan Arts’, I called it), and before that we were together in Toronto in July 1993 at the 60th birthday party of John O’Neill, who supervised us both at York’s graduate programme in Social and Political Thought. As Gary approached the window of the café, I hesitated a moment before heading out greet him; I wanted to observe his uncertainty over whether he’d found the right place. At some point in our conversation over lunch he presented me with Stephen Riggins (SR)’s The Pleasures of Time: Two Men, A Life (PT) to ask if I’d review it for the SRB. A few months ago I’d browsed through it at the Chapters on Robson and found SR’s fragmentary diary-like entries fascinating. The moving story of his 30-plus years with his partner, Paul Bouissac (PB), was reminiscent of the 15-plus years I’ve spent with
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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 | 0.004 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.060 | 0.029 |
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".