Students Doing Conflict Resolution? A Case Study in a Free School
Bibliographic record
Abstract
While the challenges of improving young people's citizenship skills seem to lie in the hands of schools, studying alternative ways of teaching conflict resolution could benefit current educational systems. Judicial committees – a democratic approach to conflict resolution – like those practiced in free schools – schools where students and teachers are largely entitled to similar rights and obligations – represent such an alternative. The present inquiry is an ethnographic case study that draws upon complexity thinking. It aims at understanding students' experiences during free school judicial committees. It argues that, in a school where students enjoy a significant amount of freedom, students interacted in many ways. This gave rise to some conflicts. To tackle them, students followed various procedures inherent to judicial committees. During these activities, students mostly experienced a combination of feelings while engaging in conflict resolution processes and modifying their conflict resolution skills. The study ends by arguing that conventional schools can draw upon the principles associated to judicial committees to further how they teach conflict resolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.009 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".