Bibliographic record
Abstract
During the 1880s a number of Oxford students took an interest in political economy, many of whom as students of history developed what has come to be seen as a ‘historical economics’ distinct from the kind of economics fostered in Cambridge by Alfred Marshall. Prominent among these was William Ashley, and also Arnold Toynbee, whose posthumous Lectures on the Industrial Revolution for the first time linked early nineteenth-century political economy directly to the idea of an ‘industrial revolution’, and interpreting British historical experience in these terms. Ashley had attended Toynbee’s lectures in Oxford and then co-edited them into the book; this chapter examines the kind of arguments that Toynbee put forward in the light of Ashley’s own early writings, and his teaching in Toronto and Harvard, where he was founding Professor of Economic History. Detailed examination of Toynbee’s text suggests that Ashley had a larger role in shaping it than hitherto realised, and this insight is then employed to make sense of Ashley’s subsequent ambivalence about contemporary economics, and his occasional disparagement of any economic reasoning that moved beyond the work of John Stuart Mill’s Principles of Political Economy (1848).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".