Conjuring (divine) authority: the myth of the 'found' text
Bibliographic record
Abstract
In this study, I classify and examine a literary device that I term ‘the myth of the found text’ so as to explore how such stories operate to authorize and reinforce, especially religious, authority. Here I contend that individuals or groups in specific socio-historical contexts construct stories of found texts as a kind of conjuring trick, one that functions to confer the storyteller’s power and stature. By appealing to the authority of an ancient text allegedly newly recovered, these mythmakers are able to situate social programs and religious reforms in an imagined, ideal antiquity—an exemplary past. The creation and telling of such myths can thus be seen as a political manoeuvre, a manoeuvre that constructs an authority (the ‘found’ text) that is then cleverly protected from contestation. While we may be quick to impugn such strategies, they have much in common, I argue, with ‘religion’ and with scholarship itself.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".