À la recherche du 1% : que nous apprennent les travaux d’Atkinson, Piketty et Saez sur la concentration des hauts revenus ?
Bibliographic record
Abstract
Les inégalités de revenu se font croissantes dans la plupart des pays avancés et la richesse se concentre davantage au sommet de la pyramide sociale. Les deux principaux courants de pensée, l’école institutionnaliste et l’école du marché, peinent à expliquer pourquoi la hausse des inégalités de revenus se concentre principalement dans le centile le plus fortuné. Partant de ce constat, un nouveau courant de pensée s’est plutôt concentré, à l’instigation entre autres d’Atkinson, Piketty et Saez, sur les statistiques fiscales des très hauts revenus, fortement sous-estimés dans les enquêtes par sondage. Cet article présente une synthèse critique de leurs hypothèses, de leur méthodologie et de leurs résultats.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".