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Record W4413398350 · doi:10.1080/01402382.2025.2543204

Pathways to politics: a sequence analysis of political apathy and involvement

2025· article· en· W4413398350 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWest European Politics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsInnovation Cluster (Canada)
FundersRheinische Friedrich-Wilhelms-Universität BonnDeutsche Forschungsgemeinschaft
KeywordsPoliticsApathySequence (biology)Political sciencePolitical economySociologyPsychologyLawCognitionBiologyNeuroscienceGenetics

Abstract

fetched live from OpenAlex

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.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.049
GPT teacher head0.331
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it