The role of reform in revolutionary struggles: advancing imaginable, semi-imaginable, and unimaginable reforms to work towards prison abolition
Bibliographic record
Abstract
This paper explores how different types of reform can be used to progress short-, medium-, and long-term abolitionist goals. I begin by examining liberal reform – or reformist reforms – and how they often end up reifying imprisonment. I juxtapose liberal reform to the proposed abolitionist reform typology, consisting of imaginable, semi-imaginable, and unimaginable reforms. Drawing on the community organizing of the Criminalization and Punishment Education Project (CPEP) – a volunteer-based activist group working in Ottawa, Ontario, Canada – I demonstrate how different types of reforms can be pursued by abolitionists simultaneously: imaginable reforms that reduce the harms and use of carceral spaces and practices; semi-imaginable reforms that work to divert and decarcerate people from custody; and unimaginable reforms that replace oppressive structures with caring and compassionate ones. I also explore the pitfalls, possibilities, and tensions within each approach to reform within revolutionary struggles. This paper seeks to cover the possibilities and pitfalls of different types of reform and envision how they can be used in concert to progress prison abolition.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".