Bibliographic record
Abstract
Abstract Thomas Piketty argues that economists need to more seriously engage with history to understand inequality. In his two books on capitalism, Piketty does just that. But what type of history? This essay argues that Piketty, following the example of the Annales School and Braudel's The Mediterranean , has produced a powerful “descriptive” history, a still underappreciated form of work that is often incorrectly contrasted with analytical history. Piketty's insights stem from the power of description in telling us “what was the case,” as Allan Megill argues, and thus precedes causal explanation. When it comes to change over time, Piketty follows the model of eventful temporality that William Sewell has proposed. In contrast to positivist social science, which is built around deep constants over time, Piketty understands that the forces of history subject even seemingly stable structures to change. For this reason, he also believes it is possible to overcome the deep inequalities that have long existed in capitalism.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.042 |
| Scholarly communication | 0.011 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.019 | 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".