QUANTUM PHYSICS AND THEOLOGY: JOHN POLKINGHORNE ON THOUGHT EXPERIMENTS
Bibliographic record
Abstract
Abstract Thought experimentation is part of accepted scientific practice, and this makes it surprising that philosophers of science did not seriously engage with it for a very long time. The situation changed in the 1990s, resulting in a highly intriguing debate over thought experiments. Initially, the discussion focused mostly on thought experiments in physics, philosophy, and mathematics. Other disciplines have since become the subject of interest. Yet, nothing substantial has been said about the role of thought experiments in nonphilosophical theology. This paper discusses the role of thought experiments in Christian theology in comparison to their role in quantum physics, as mentioned by John Polkinghorne in Quantum Physics and Theology. We first look briefly at the history of the inquiry into thought experiments and then at Polkinghorne's remarks about the role of thought experimentation in quantum physics and Christian eschatology. To determine the actual importance of thought experiments in Christian theology a number of new examples are introduced in a third step. In the light of these examples, in a fourth step, we address the question of what it is that explains the cognitive efficacy of thought experiments in quantum physics and Christian theology.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.073 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| 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".