Bibliographic record
Abstract
Abstract: This paper provides not only a systematic account of the theology and ethics of Peter Paris, but also a critical interpretation of his thought. It identifies racism as the major problem that has engaged his academic career and the theological-ethical methodology he has developed to understand and explain it. He is been able to do all this in ways that evade and challenge the American theological enterprise. The primary theme of Paris's work is evading epistemology-centred ethics, exposing racism and injustice, and accenting the transformation of the structures of domination and subordination in the light of an ethical ideal, which is usually the thwarting of evil or actualization of human potentialities. In doing this, he converts ethics into a positive science of social critique and cultural investigation of the social crises of the United States. The importance of this paper goes beyond interpreting Paris's thought, as it will be useful to scholars teaching ethics in general and African-American ethics in particular. Paris's evasion of ethics is rooted in the black religious tradition of ethical critique of American society in order to expose its moral limits and remind it of its blindnesses, as W.E.B. Du Bois informed us. The paper—in also locating the thought of Paris in the deep ethos that informed the spirituals—reveals another major dimension of African-American ethical scholarship. Most importantly, by carefully discussing the ethical methodology of Paris in particular, this paper clarifies that of African-American ethicists in general.
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.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.071 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.010 |
| 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".