Experiential Learning in Circles of Safety: Reflections on Walls to Bridges and Dewey’s Theory of Experience
Bibliographic record
Abstract
This paper discusses a Winnipeg-based community-university partnership structured as a set of interlinked “Circles of Safety” to support criminalized women while incarcerated and after their release. The four Circles include university, community, social co-operatives, and corrections; these circles contain the action research activities we are undertaking to provide greater safety for women transitioning from prison into the community. The motivation for our prison education program, which draws on the American Inside-Out Program and the newer Canadian Walls to Bridges Program, comes from these four directions and is energized by a belief in the human right to education. This paper argues that the success of both American and Canadian programs is explained by an approach to prison education that is complementary to John Dewey’s principles of educative experience, specifically principles based on continuity and interaction. Adapting and extending Dewey, the Circles of Safety model described in this paper maintains the value of experiential learning, which is defined as learning in situations that begin with the experience that the learners already have and subject matter that is within the scope of their ordinary life-experience, leading to their formation of purpose.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.075 |
| Scholarly communication | 0.013 | 0.020 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.005 | 0.009 |
| 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".