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Record W3087229121 · doi:10.1007/s10814-020-09147-9

Killing the Priest-King: Addressing Egalitarianism in the Indus Civilization

2020· article· en· W3087229121 on OpenAlexfundno aff
Adam S. Green

Bibliographic record

VenueJournal of Archaeological Research · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
FundersMcDonald Institute for Archaeological ResearchBiotechnology and Biological Sciences Research CouncilYork University
KeywordsIndusCivilizationEgalitarianismUrbanismPoliticsPower (physics)Ruling classSociologyPolitical economyHistoryAncient historyArchitectureArchaeologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract The cities of the Indus civilization were expansive and planned with large-scale architecture and sophisticated Bronze Age technologies. Despite these hallmarks of social complexity, the Indus lacks clear evidence for elaborate tombs, individual-aggrandizing monuments, large temples, and palaces. Its first excavators suggested that the Indus civilization was far more egalitarian than other early complex societies, and after nearly a century of investigation, clear evidence for a ruling class of managerial elites has yet to materialize. The conspicuous lack of political and economic inequality noted by Mohenjo-daro’s initial excavators was basically correct. This is not because the Indus civilization was not a complex society, rather, it is because there are common assumptions about distributions of wealth, hierarchies of power, specialization, and urbanism in the past that are simply incorrect. The Indus civilization reveals that a ruling class is not a prerequisite for social complexity.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.612

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.277
GPT teacher head0.357
Teacher spread0.080 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2020
Admission routes1
Has abstractyes

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