In the Pursuit of Justice: A Case Study on the Role of Service-Learning in Developing Civic Engagement among College Students in Egypt
Bibliographic record
Abstract
Service-learning is a form of experiential education that connects classroom instruction with community service for the benefits of the partners involved. While the effects of service-learning on college students are well documented in Western settings, considerably less is known about these effects in Eastern contexts. Given the current profound political changes in Egypt and the greater Arab world, this research utilized a case study design to explore the potential of service-learning for developing civic awareness among college students at a university in Northern Egypt. Findings revealed that participation in service-learning allowed students valuable opportunities to connect with others from backgrounds different from their own. Through their work in the community, students gained important civic skills, including thinking critically and addressing public problems, developing perspective-taking positions, and enhancing coping capabilities. The study outcomes suggest a cultural shift in Egypt that validates young adults as a productive segment of population thus affording them structured opportunities for civic engagement through which they could exercise their leadership skills and effect positive change in their communities. The ongoing critical engagement of students in their communities where they grapple with questions about the structural causes of inequalities in society is pivotal for service-learning to be a truly empowering learning experience.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".