À propos de Josepha Laroche, La brutalisation du monde. Du retrait des États à la décivilisation , Montréal, Liber, 2012, 184 p., glossaire, index, bibliographie.
Bibliographic record
Abstract
systèmes de partis et alignement des électeurs : une introduction, Bruxelles, Éditions de l'ULB, 2008.4. « Les clivages en politiques », Revue internationale de politique comparée, 12 (1), 2005. 5. « The Structure of Political Competition in Western Europe », West European Politics, 33 (3), 2010.6. Les applications (non exhaustives) sont variées : sociologie des mouvements sociaux (Mario Diani, « Simmel to Rokkan and Beyond.Toward a Network Theory of (New) Social Movements », European Journal of Social Theory, 3 (4), novembre 2000, p. 387-406), structuration de l'Union européenne (Stefano Bartolini, Restructuring Europe.Centre Formation, System Building, and Political Structuring Between the Nation State and the European Union, Oxford, Oxford University Press, 2005), étude de l'État providence (Maurizio Ferrera, The Boundaries of Welfare.European Integration and the New Spatial Politics of Social Solidarity, Oxford, Oxford University Press, 2005) ou encore extension de la grille de lecture à l'Europe centrale et orientale (Arne Kommisrud, Historical Sociology and Eastern European Development.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".