States of Citizenship: Contexts and Cultures of Public Engagement and Citizen Action
Bibliographic record
Abstract
Summary Drawing on case studies from the Citizenship Development Research Centre, this paper contends that mechanisms aimed at enhancing citizen engagement need to be contextualised in the states of citizenship in which they are applied. It calls for more attention to be focused on understanding trajectories of citizenship experience and practice in particular kinds of states. It suggests that whilst efforts have been made by donors to get to grips with history and context – such as DFID's Drivers of Change analyses or Sida's Power Studies – less attention has been given to exploring the implications of the dissonance between the normative dimensions of global narratives of participation and accountability, and the lived experience of civic engagement and the empirical realities of ‘civil society’ in diverse kinds of states. By exploring instantiations of citizenship in different kinds of states, the paper reflects on what citizen engagement comes to imply in these contexts. In doing so, it draws attention to the diverse ways in which particular subject‐positions and forms of identification are articulated in the pursuit of concrete social and political projects.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.033 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".