Joint Bayesian Assessment of Fine‑Tuning and Moral Arguments Boosts Credence in God

1. 01Define the thesis precisely

   completed

   Define the thesis precisely as a claim about joint Bayesian updating.

2. 02Identify assumptions and key terms

   completed

   Identify assumptions: Bayesian modeling of both arguments and independence.

3. 03Specify supporting and opposing evidence

   completed

   Specify evidence needed: Bayesian fine‑tuning support and Bayesian moral support.

4. 04Gather primary and secondary sources

   completed

   Gather sources: SEP-fine-tuning, SEP-process-theism, Wikipedia entries.

5. 05Extract claims and relevant evidence

   completed

   Extract claims: fine‑tuning Bayesian credence >0.5; no source on moral Bayesian analysis.

6. 06Evaluate source reliability and verify claims

   inconclusive

   Evaluate reliability: SEP entry is scholarly; Wikipedia is secondary; no moral evidence.

7. 07Construct the strongest supporting argument

   completed

   Construct strongest supporting argument using established fine‑tuning evidence and assumed moral evidence.

8. 08Construct the strongest opposing argument

   completed

   Construct strongest opposing argument highlighting lack of moral Bayesian data and possible dependence.

9. 09Test logical structure and assumptions

   completed

   Test logical structure: both arguments valid if premises hold; premises are contested.

10. 10Compare competing explanations

    completed

    Compare competing explanations: multiverse and non‑theistic moral realism as alternatives.

11. 11Record unresolved issues

    completed

    Record unresolved issues: absence of formal joint Bayesian model and moral likelihoods.

12. 12Produce the current assessment

    completed

    Produce the current assessment: claim remains underdetermined.

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