Self-Efficacy and Citizen Engagement in Development: Experimental Evidence from Tanzania
Bibliographic record
Abstract
Abstract Recent studies of efforts to increase citizen engagement in local governance through information campaigns report mixed results. We consider whether low levels of self-efficacy beliefs limit engagement, especially among poor citizens in poor countries. Citizens may be caught in an “efficacy trap” which limits their realization of better public goods provision. We describe results from a series of experimental studies conducted with over 2,200 citizens in rural Tanzania, in which we compare the effects of standard information campaigns with Validated Participation (VP), an intervention designed to socially validate citizens’ participation. We implement a staged approach to experimental research, seeking to balance ethical and cost concerns about field experimentation. In our main analyses, we find that VP did not lead to increased levels of self-efficacy or more active citizen behaviors relative to standard informational treatments. Nonetheless, we find some promising evidence for VP in a follow-up qualitative study with teachers. We conclude by discussing lessons from this research and directions for future investigation of the possible role of self-efficacy traps in development.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".