Database of Religious History and the Study of Ancient Mediterranean Religiosity
Bibliographic record
Abstract
As a quantitative and qualitative encyclopaedia of religious cultural history, the Database of Religious History (DRH) opens for historians new and exciting avenues of research. Some of these avenues complement and cohere with existing research practices, while others supplement and even expand the horizons of scholarly inquiry and imagination. In this article I explore the function and utility of the DRH when studying a specific geo-temporal locale (namely, the ancient Mediterranean) and the many expressions of religion that exist within that historical space (namely, ancient Mediterranean religiosity). My aim is twofold. On the one hand, I demonstrate the utility of the DRH, specifically showing how this database project confronts, even embraces, the challenges posed by historical sources. On the other hand, I highlight promising avenues that are opened up by the DRH in addressing a specific problem within the scholarly study of ancient Mediterranean religiosity (namely, the question of whether we should we speak of religion or religions in the ancient Mediterranean). My discussion concludes with reflection on the intersection of the DRH with cognitive historiography, specifically with respect to the inherent interdisciplinarity of both projects.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".