La non-participation politique des jeunes : Une étude des barrières temporaires et permanentes de l'engagement
Bibliographic record
Abstract
Résumé.Avec une méthodologie double, nous portons notre attention sur un groupe très peu étudié : les jeunes non-engagés. Grâce à des entrevues, nous distinguons quatre types de non-engagés: les critiques, ceux qui manquent de ressources politiques, les occupés, et ceux en attente de mobilisation. Lescritiquesne représentent qu'une minorité des non-engagés, alors que les jeunes manquant de ressources sont plus nombreux. Cette étude démontre qu'une grande proportion de jeunes présente un potentiel d'engagement futur et que c'est principalement des barrières temporaires qui réduisent leur niveau d'engagement. L'analyse quantitative dévoile des variations d'attitudes, de profils démographiques et de volontés d'engagement entre types de non-engagés. Les non-engagés ne sont donc pas un groupe homogène. Abstract.With a two-pronged methodology, this article takes a closer look at an understudied group: the disengaged youth. Using interviews, we discern four different types within this disengaged group: the criticals, those lacking political resources, the busy and those waiting for mobilization. The ‘criticals’ constitute only a minority of the disengaged group, while the young people who lack political resources are more common. Most importantly, a great proportion of young people show a certain potential for engagement. The quantitative analysis reveals that these types resemble distinct attitudinal and demographic profiles, and differ in their future willingness to participate. Thus the non-engaged are not a monolithic group.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".