Found But Not Lost: A Skeptical Note on the Document Discovered in the Temple under Josiah
Bibliographic record
Abstract
In this paper I look at the famous story of the finding of the “book of the law” in the temple during the reign of Josiah. Adopting a pragmatic/plausible approach and keeping in mind the biblical testimony about earlier circumstances in Judah, I argue that the story as we have it lacks inherent plausibility and should be rejected as an etiological invention, whether or not of the time. None of the various scenarios that could explain its disappearance can also serve to explain why it remained hidden for so long, only to be discovered at just the right moment to provide a willing Josiah with the justification to begin a cultic reform program.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.039 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.008 | 0.025 |
| Insufficient payload (model declined to judge) | 0.003 | 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".