What Makes Us Human? The Interdisciplinary Challenge to Theological Anthropology and Christology
Bibliographic record
Abstract
Abstract: In this paper I argue for a theology that ought to be present in the interdisciplinary conversation that constitutes our public discourse, including the secular academy. I contend that the question of what makes us human can be answered only by pointing to the central theme of self and personhood. Already in early hominid evolution, the evolution of some of our most distinctive traits like consciousness, imagination, sexuality, moral awareness, language, and the religious disposition present us with a robust notion of embodied personhood. This strongly affirms the emergence of symbolic religious behaviour in our species. Ultimately I argue how a responsible account of the evolution of human distinctiveness, both theologically and scientifically, makes it possible to reach deep into theology and ask the ontological question about the personhood and identity of Jesus, as well as the ethical question why we should do what Jesus did.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.099 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".