Das Tocqueville Problem: Individualism and Equality between<i>Democracy in America</i>and<i>Ancient Regime</i>
Bibliographic record
Abstract
This article argues that there is a major inconsistency between Tocqueville's arguments about individualism and equality of conditions as described in his books Ancient Regime and the Revolution and Democracy in America. In the latter, which is the basis for conventional analysis of Tocqueville in America, individualism is taken as a spontaneously emerging feature of the modern, enlightened society, heralding the European future. In the Ancient Regime, however, leveling individualism is conceptualized as a by-product of the centralizing political dynamic of the modern European state, crushing all intermediate sources of social authority. If we accept this theory, America would be the last place one would expect to find individualism or equality, because the American institutions of a modern, centralized state were much weaker than in Europe, yet Tocqueville does look to the United States as such an example. It is argued in this article that the different genealogies of individualism developed by the French thinker cannot be satisfactorily reconciled; the alternative approach suggested here is to combine Tocqueville's analysis from Ancient Regime with modern historical research about early England and America which confirm them, making the analysis of individualism from Democracy in America largely superfluous.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".