Behind the Veil: Mysticism and the Reply to Hiddenness in the Work of Travis Dumsday
Bibliographic record
Abstract
Ever since J. L. Schellenberg formulated his infamous atheistic argument from hiddenness in his 1993 book Divine Hiddenness and Human Reason, the problem of divine hiddenness--the question of why a good God would hide Himself, even from those actively seeking Him--has troubled theists. Schellenberg's argument from hiddenness has proven notoriously difficult for theists to answer, and perhaps this is why it is now second only to the problem of evil in popularity with atheists. While many theists have tried to find an adequate answer to the problem of hiddenness, and many have made good attempts, no response has been quite complete. Many such replies have been made by Dr. Travis Dumsday of the Concordia University of Edmonton. Dumsday has written prolifically on the subject of divine hiddenness, but in this paper I will look at only three of his replies to Schellenberg's argument from hiddenness. These three responses, while each insufficient on their own, become a far more formidable reply to the problem of hiddenness when combined and synthesized around a more mystic conception of God imported from the Christian mystic tradition. Drawing upon the mysticism of Saint Francis of Assisi and the rigorous philosophy of Dumsday, I argue that the great mystery that we call God remains hidden in order to preserve the well-being of nonbelievers, and that He does indeed reveal Himself, but only to those who cultivate the requisite level of moral virtue and seek Him diligently.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.061 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.015 | 0.028 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".