The emerging field of spiritual neuroscience: An interview with Mario Beauregard, PhD. Interview by Sheldon Lewis.
Bibliographic record
Abstract
Mario Beauregard, PhD, a cognitive neuroscientist at the University of Montreal in Canada, has been studying the neuroscience of consciousness and mystical experience for many years, including a study investigating the brain activity of Carmelite nuns, for which he has received considerable media attention. He conducted postdoctoral research at the University of Texas and the Montreal Neurological Institute at McGill University. He was selected by the World Media Net, a consortium of major daily newspapers in Europe and North America created at the turn of the new millenium as one of "100 Pioneers of the 21st Century." He is co-author with Denyse O'Leary of the book The Spiritual Brain: A Neuroscientist's Case for the Existence of the Soul (HarperOne, 2007). Dr Beauregard was recently interviewed by Sheldon Lewis, editor in chief of Advances.
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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 | 0.007 | 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 | 0.013 | 0.007 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.011 | 0.030 |
| Insufficient payload (model declined to judge) | 0.005 | 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".