Identifying abolitionist alignments in community psychology: A path toward transformation
Bibliographic record
Abstract
Psychology is grounded in the ethical principles of beneficence and nonmaleficence, that is, "do no harm." Yet many have argued that psychology as a field is attached to carceral systems and ideologies that uphold the prison industrial complex (PIC), including the field of community psychology (CP). There have been recent calls in other areas of psychology to transform the discipline into an abolitionist social science, but this discourse is nascent in CP. This paper uses the semantic device of "algorithms" (e.g., conventions to guide thinking and decision-making) to identify the areas of alignment and misalignment between abolition and CP in the service of moving us toward greater alignment. The authors propose that many in CP are already oriented to abolition because of our values and theories of empowerment, promotion, and systems change; our areas of misalignment between abolition and CP hold the potential to evolve. We conclude with proposing implications for the field of CP, including commitments to the belief that (1) the PIC cannot be reformed, and (2) abolition must be aligned with other transnational liberation efforts (e.g., decolonization).
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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 | 0.040 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.010 | 0.115 |
| Scholarly communication | 0.017 | 0.039 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.005 | 0.014 |
| 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".