A systematic assessment of 'Axial Age' proposals using global comparative historical evidence
Bibliographic record
Abstract
Proponents of the Axial Age contend that parallel cultural developments between 800 and 200 BCE in what is today China, Greece, India, Iran, and Israel-Palestine constitute the global historical turning point towards modernity. While the Axial Age concept is well-known and influential, deficiencies in the historical evidence and sociological analysis available have thwarted efforts to evaluate the Axial Age concept’s major global contentions. As a result, the Axial Age concept remains controversial. Seshat: Global History Databank provides new tools for examining this topic in social formations across Afro-Eurasia during the first two millennia BCE and first millennium CE, allowing scholars to empirically evaluate the many varied— and contrasting—claims put forward about this period. Our systematic investigation undercuts the notion of a specific 'age' of axiality limited to a specific geo-temporal localization. Critical traits offered as evidence of an axial transformation by proponents of the Axial Age concept are shown to have appeared across Afro-Eurasia hundreds and in some cases thousands of years prior to the proposed Axial Age. Our analysis raises important questions for future evaluations of this period and points the way towards empirically-led, historical-sociological investigations of the ideological and institutional foundations of complex societies.
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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 | 0.089 | 0.160 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.038 | 0.026 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".