Reorienting Archeological Research on the Maya: Toward a New Definition of Polity
Bibliographic record
Abstract
Classic Maya Polities of the Southern Lowlands investigates Maya political and social structure in the southern lowlands, assessing, comparing, and interpreting the wide variation in Classic period Maya polity and city composition, development, and integration. Traditionally, discussions of Classic Maya political organization have been dominated by the debate over whether Maya polities were centralized or decentralized. With new, largely unpublished data from several recent archaeological projects, this book examines the premises, strengths, and weaknesses of these two perspectives before moving beyond this long-standing debate and into different territory. The volume examines the articulations of the various social and spatial components of Maya polity—the relationships, strategies, and practices that bound households, communities, institutions, and dynasties into enduring (or short-lived) political entities. By emphasizing the internal negotiation of polity, the contributions provide an important foundation for a more holistic understanding of how political organization functioned in the Classic period. Contributors include Francisco Estrada Belli, James L. Fitzsimmons, Sarah E. Jackson, Caleb Kestle, Brigitte Kovacevich, Allan Maca, Damien B. Marken, James Meierhoff, Timothy Murtha, Cynthia Robin, Alexandre Tokovinine, and Andrew Wyatt.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".