Bibliographic record
Abstract
In August 2002 prison activists and scholars from the United States, Canada, Australia, and across the African continent travelled to Lagos, Nigeria, for the Tenth International Conference on Penal Abolition (ICOP A X). Coordinated by Viviane Saleh-Hanna, then a staff member at Prisoners Rehabilitation and Welfare Action, the conference challenged those of us involved in prison activism and research to examine our unstated Western bias.Although often extremely knowledgeable about prison systems and anti-prison movements in the United States, Canada, and Europe, few of us knew anything about penal systems in West Africa.Indeed, we had most commonly defined the concerns, priorities, and goals of prison studies and antiprison activism with no regard for the experiences of scholars and activists in the global South.Shortly before the conference the US government issued a warning suggesting that American visitors might not be safe in Nigeria, due to ethnic and religious conflict, and that Nigerian Airways was not up to international air safety standards, further discouraging travel.These warnings remind us that the lack of scholarly and activist engagements across the First World/Third World divide is a reflection of broader ideological and structural forces.Despite the shrinking of the globe and the emergence of a border-crossing cosmopolitan elite, significant barriers remain to meaningful and transformative transnational engagements in the field of prison xxi
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.293 | 0.310 |
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".