WHAT IS OUR “CANON”? HOW AMERICAN INTELLECTUAL HISTORIANS DEBATE THE CORE OF THEIR FIELD
Bibliographic record
Abstract
These selected excerpts from a conversation now running nearly a quarter-century about The American Intellectual Tradition: A Sourcebook exemplify the efforts made by specialists in American intellectual history to decide just what constitutes the core of their field. An anthology designed for undergraduates has practical limitations, to be sure, that prevent its table of contents from ever serving as a complete map of a field. Specific research questions, not arguments over canons, properly remain the deepest center of gravity of any cohort of scholars. But assignments to students are one important indicator of what scholar–teachers take to be important, and these assignments are not unrelated to choices these same individuals make about the topics of their monographic contributions. Hence the lively correspondence that my coeditor, Charles Capper, and I have carried on with dozens of colleagues concerning the six editions of the only collection of sources for this field currently in print offers a window on how American intellectual history has changed in the last generation and what are its current directions.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.027 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".