Défaites politiques et trajectoires d’engagement : le choc moral de l’année 2016 pour les pétistes de Belo Horizonte
Bibliographic record
Abstract
Au Brésil, le Parti des travailleurs (PT) sort considérablement amoindri de l’année 2016 : relégué dans l’opposition après la destitution de Dilma Rouseff, il est durement défait aux élections municipales. À partir d’une enquête de terrain menée à Belo Horizonte, cet article interroge des militant·es pétistes sur leur perception de cette relégation soudaine, appréhendée ici sous le prisme de la défaite politique. Mon objectif est d’identifier, de contextualiser et de mesurer le potentiel mobilisateur de ce type d’événements sur les trajectoires d’individus activement engagés dans la campagne électorale du PT en vue des élections générales brésiliennes de 2018. Depuis une entrée par l’engagement, je mobilise les concepts de bifurcation et de choc moral pour analyser les incidences d’une telle relégation politique sur les trajectoires de vie en matière d’engagement militant.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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; 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".