Bibliographic record
Abstract
Claims that Herodotus reveals himself as a proto-biographer, let alone as a proto-feminist, are not yet widely accepted. To advance these claims, I have selected one remarkable woman from one side of the Greco-Persian Wars whose activities are recounted in his Histories. Critically it is to a near contemporary, Heraclitus, to whom we attribute the maxim êthos anthropôi daimôn (ἦθος ἀνθρώπῳ δαίμων) —character is human destiny. It is the truth of this maxim—which implies effective human agency—that makes Herodotus’ creation of historical narrative even possible. Herodotus is often read for his vignettes, which, without advancing the narrative, color-in the character of the individuals he depicts in his Histories. No matter, if these fall short of the cradle to grave accounts given by Plutarch, by hop-scotching through the nine books, we can assemble a partially continuous narrative, and thus through their exploits, gauge their character, permitting us to attribute both credit and moral responsibility. Arguably this implied causation demonstrates that Herodotus’ writings include much that amounts to proto-biography and in several instances—one of which is given here—proto-feminism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.004 | 0.010 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".