Human Aging as a Creational Good: Interactions between Theology and Molecular Biology
Bibliographic record
Abstract
This is an accepted article with a DOI pre-assigned that is not yet published.A Christian theology of human aging faces significant challenges. First, aging receives far less theological attention than the heavily related and well-established themes of creation, sin, death, and imago Dei. Second, Christian theology discordantly supports two fundamental yet polarized claims: that human aging is a good of creation, and that it is an effect of humanity’s fall. Third, it lags in its engagement with the science of aging. This paper counteracts these obstacles by integrating Christian theology with molecular biology. Aging generating lifespan (“human biological aging”; HBA) is distinguished from aging leading to life-expectancy. Intrinsic molecular pathways driving HBA are orchestrated, functional systems, spanning multiple biological strata. Surprisingly, aging processes are indivisible from life, health, and growth processes. These considerations build a case for understanding HBA as a good of divine creation, clarify interpretations of the consequences of humanity’s fall, challenge transhumanist aspirations of age-reversal or cybernetic immortality, and promote a holistic view of human life through time.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".