Mode over Matter: Response to Hughes, <i>From Seminary to University</i>
Bibliographic record
Abstract
The story Aaron Hughes tells in From Seminary to University (2020) is at once archival and timely, not because it presumes to transport the past into the present or mine for prescriptive insights from thinkers long gone but because it “provide[s] a historical work that accounts for ‘how’ as opposed to ‘what’” (13). In presenting a narrative arc for the study of religion in Canada, the book offers a model of how nuanced historiography might attend to contemporary questions (both field-specific and more broadly) without making the past “about” or “for” us. Avoiding the trappings of recovery work as well as retrospective projection, Hughes considers the archive on its own terms while remaining cognizant of the fact that it never speaks for itself. This brief response essay greets the occasion the book provides to think about the structural framework that shapes the “how” of an academic discourse.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.016 | 0.029 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".