Political Context and Political Participation Across the Lifespan in Africa
Bibliographic record
Abstract
Abstract Gerontologists have long documented how age is associated with political participation. However, few studies have considered how macrocontextual factors shape participation across the life span. Moreover, very few studies have dealt with political engagement and aging in emerging democracies, including those in Africa. This study addresses those gaps, integrating the most recent three waves of Afrobarometer survey data (2011–2018) with country-level data from the freedom house (i.e. freedom index). Findings reveal that, at the individual level, an age gap widens for engagement in protests and shrinks for electoral and non-electoral political participation. When the political context is considered, however, we find that political freedom softens the drop-off of protest behavior at later ages. For electoral and non-electoral political participation, we find that freer countries lessen the expected growth in engagement across the life span. The study implies that political oppression shapes the links between age and political behaviour, but the processes seem different depending on whether they are engaging in risky (where the age gap widens) or non-risky (where the age gap shrinks) political forms of engagement.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".