Walls to Bridges: Evolving Our Work Within Carceral Spaces by Rupturing Racism and Oppression Through a Participatory Process
Bibliographic record
Abstract
This article examines the collaborative process undertaken by Walls to Bridges (W2B) collective members and facilitators in planning and hosting the Evolving Our Work symposium as part of the W2B's 10 th Anniversary virtual celebrations, as well as provides refl ections on the collaborative planning of the event.Given our visioning process moving forward in the next chapter of W2B, we build on an already established pedagogical body of work that has provided a guiding blueprint for visioning, collaborating, and organizing social justice frameworks for those inside and outside carceral spaces.As part of the planning process for this event, group members asked guiding questions that sought queries into where we see this work going in the future and potential challenges for evolving this work.Our eff ort to frame these questions was guided by working through decolonial frameworks that centered the critical importance of Indigenous resurgence, Land Back organizing, and the Black Lives Matter movement as pedagogical practice for informing solidarity between these two movements, as well as examining tensions.A key focus of this article queries the importance of self-refl ection as an ontological teaching and learning decolonizing practice in creating W2B courses and informing race relations with other racialized groups inside and outside carceral spaces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".