Institutions, innovation, and industrialization : essays in economic history and development
Bibliographic record
Abstract
Introduction 1 The Enlightened Economist Avner Greif, Lynne Kiesling, & John V. C. Nye (Editors) 1Neither Feast nor Famine 7 England before the Industrial Revolution Cormac O'Grada 2Progress, Useful Knowledge , and the Origins of the Industrial Revolution 33 Joel Mokyr I Institutions 3Coercion and Exchange 71 How Did Markets Evolve? Avner Greif 4Meat Consumption in Nineteenth-Century New York 97 Quantity, Distribution, and Quality, or Notes on the Antebellum Puzzle Gergely Baics 5Funding Empire 129 Risk, Diversification, and the Underwriting of Early Modern Sovereign Loans Mauricio Drelichman and Hans-Joachim Voth 6Establishing a New Order 149 The Growth of the State and the Decline of Witch Trials in France Noel D. Johnson, Mark Koyama, and John V. C. Nye II Innovation 7Increasing Market Concentration in British Banking, 1885 to 1925 179 Fabio Braggion, Narly R.D. Dwarkasing, and Lyndon Moore 8The Catapult of Riches 201 The Airplane as a Creative Macroinvention Peter B. Meyer 9England's Eighteenth-Century Demand for High-Quality Workmanship 225 Evidence from Apprenticeship, 1710-1770 Karine van der Beek 10A Growth Agenda for Economic History 245 Rick Szostak III The Industrial Revolution 11Amidst Poverty and Prejudice 277 Black and Irish Civil War Veterans Hoyt Bleakley, Louis Cain, and Joseph Ferrie 12How Britain Lost Its Competitive Edge 307 Competence in the Second Industrial Revolution Ralf R. Meisenzahl 13Regulating Child Labor 337 The European Experience Carolyn Tuttle and Simone A. Wegge 14Decomposing the Wage Gap 379 Within- and Between-Occupation Gender Wage Gaps at a Nineteenth-Century Textile Firm Joyce Burnette 15The Context of English Industrialization 397 Eric Jones Contributors 411 Index 417
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".