Massification and its Critique in the Nineteenth Century History of Ideas: József Eötvös on Popular Meanings and Public Life
Bibliographic record
Abstract
Writing after the failure of the 1848 Hungarian revolution, József Eötvös, himself a prominent politician and novelist, grappled with the sources of the failure and conditions of success of social and political reforms. In his monumental work, The Dominant Ideas of the Nineteenth Century and their Impact on the State, he proposed that in order to understand the behaviour of the masses and design social and political reforms that will have popular support, one needed to understand the meanings people assigned to popular ideas—as opposed to meanings assigned to them by theorists. Popularity, in this approach, had three components: ideas around which people rallied, emotions that connected them to these ideas, and actions people undertook in their name. The way towards understanding these components was to understand the culture of the people in its various manifestations, from popular religiosity to literary and material culture. By re-reading Eötvös’s work focusing on his conception of popular ideas, this paper investigates how the longstanding tension between popularity and the distrust in populism was articulated in a classic of nineteenth century central European political thought.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".