Against the churn: institutionalization, transformation, and restorative justice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drawing on twenty interviews conducted in 2022 with restorative justice practitioners and transformative justice advocates in Winnipeg, Manitoba, we examine how restorative justice navigates the churn of institutionalization. In Manitoba, this churn is strengthened through the creation of the Restorative Justice Centre as a government clearinghouse for referrals and funding. Simultaneously, anti-institutional philosophies of defunding, abolition, and decolonization have seen recent increased uptake among segments of the population. Based on our interviews, we argue that restorative programming in Manitoba has institutionalized to a degree that there is little optimism toward aligning or synthesizing restorative and transformative justice. But this does not mean each must remain its own solitude. Focusing on restorative justice and the threat of further institutionalization, we suggest restorative practitioners anchor themselves to transformative ideals, while also using transformative justice as a horizon by which they might seek to correct course when the pull of institutionalization becomes increasingly strong.
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.
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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it