Maximizing Animal Theology: Maximus the Confessor on the Value of Non-Human Animals and the Human Calling
Bibliographic record
Abstract
Abstract: This article adds to the growing body of work regarding the place of animals within Christian doctrine through engaging with the theological writings of Maximus the Confessor. In this article I shall do two things. First I shall argue that the theology of Maximus makes three claims that have significant bearing on how we can understand non-human animals: (1) all creatures made by God have an inherent worth and value based on God's creative and providential acts, as well as Maximus's logoi theology, (2) these same creatures are included in God's redemptive concerns, as shown by their presence within the shared goal of deification for all creation, and (3) humans have a unique calling in helping to achieve such redemption and this sanctifying role constitutes a necessary part of what it means to be human. Second, on the basis of these ideas I shall then demonstrate how such ideas create direct implications for how Christians might respond to intensive industrial farming of non-human animals, an institution that will be shown to be at great odds with the human calling toward sanctifying creation. Given such a state, the presence of factory farming is an institution that the theology of Maximus suggests is highly problematic and stands in need of serious ethical reflection.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.052 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 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".