Translational Transnational Advocacy against Capital Punishment: A Role for the Holy See
Bibliographic record
Abstract
Networks of social activists can span sovereign borders, seeking to affect human rights policy change within an individual country. Keck and Sikkink argue that such advocates are most effective when they champion a vulnerable population. This poses a problem for transnational advocates of death penalty abolition, because persons guilty of serious crimes are not, intuitively, vulnerable people. The Catholic Church, as a member of the abolition network, attempts to alter discourse on capital punishment such that guilt does not preclude vulnerability. This article examines statements of the Holy See as one way of understanding the Church's contribution to the transnational abolition movement. By emphasising humans' vulnerability before God, treatment of violent criminals in the Bible, and the importance of a consistent ethic of life, the Holy See works to prevent the conflation of criminal guilt with moral invulnerability.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.024 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".