Pathways to politics: a sequence analysis of political apathy and involvement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Understanding inequality in political involvement is a core goal of political science. Previous research has examined specific life-course influences, but there is limited knowledge about the diverse trajectories young citizens follow to become politically engaged or apathetic. This study employs sequence analysis to identify prevailing trajectories of political involvement from adolescence to young adulthood in Germany and the United Kingdom. For a surprisingly large share, their political future of either apathy or involvement is already determined by age 17, or even as early as age 11. Only about 19% develop involvement between age 17 and 25 and only 24% between age 11 and 15. Studying predictors of individual trajectories points to strong parental influences, while personal experiences can foster later involvement for a sizeable sub-group. These results show an under-appreciated diversity of political socialisation trajectories and point to an urgent need to study the interaction of parental and personal factors shaping them.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it