Epistemology or Self-Delusion? A Final Word on Evaluating Religious Truth Claims
Bibliographic record
Abstract
Click to increase image sizeClick to decrease image size Acknowledgments We wish to thank Dr. Rosenblith for taking the time to respond to our initial comments on her academic work. Although we disagree with the tenability of her ambitious aim to evaluate religious truth claims, we genuinely appreciate the dialogue. We also wish to thank the editor of Religion and Education, Dr. Michael Waggoner, for facilitating this format in the journal. Additional informationNotes on contributorsPhilip PetersonPhilip Peterson is an instructor in the Faculty of Education at the University of New Brunswick. His scholarship focuses on epistemology and the philosophy of science. E-mail: ppeterso@unb.caEmery J. Hyslop-MargisonEmery J. Hyslop-Margison is Professor/Research Coordinator in the Faculty of Education at the University of New Brunswick. He has published widely in the philosophy of education and critical work studies. E-mail: ehyslopm@unb.ca
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".