Cultivated Participation: Looking Closer at the Relationship Between Education and Participation<sup>1</sup>
Bibliographic record
Abstract
Researchers have taken aim at the well‐established correlation between higher education and political participation, arguing much of the relationship is spurious. This has created an ongoing debate around what role, if any, education has in supporting participation, and continued questions around what underpins this relationship. Drawing on 63 semi‐structured interviews with young Canadians who went to school in low‐, mid‐, and high‐socioeconomic areas of Vancouver, I argue we can better answer these questions if we look at the influence of higher education in terms of a trajectory instead of an isolated treatment. Within these trajectories, I identify participatory social contexts (social contexts that produce participation as a desirable and expected activity) as key mechanisms that help develop dispositions for political participation. Participatory social contexts are more available to those on a trajectory of higher education, yet the experience of higher education itself appears to be of minor importance to participation.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".