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Record W2328060248 · doi:10.1017/s0959774314000626

Ruins in Pre-Columbian Maya Urban Landscapes

2014· article· en· W2328060248 on OpenAlexaff
Christina T. Halperin

Bibliographic record

VenueCambridge Archaeological Journal · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMayaWildernessTemporalitiesArchaeologyUrbanismDynamismHistoryGeographyArchitectureAncient historyAnthropologySociology

Abstract

fetched live from OpenAlex

There is a growing recognition that ancient cultures actively reworked their own pasts (and thus their futures) by reusing and modifying relics and ruined buildings. In the Maya area, architectural ruins of the Pre-Columbian past are often considered as isolated from major centres or as subsumed by new architectural constructions. In contrast, this article examines recent survey and excavations from the North-central sector of Tayasal, Guatemala, where I document the ways in which common peoples from a Terminal Classic (c. ad 800–900/950) neighbourhood lived amongst the ruins of a Late Preclassic monumental past (c. 300 bc–ad 300). Conceptions of such ruins are explored through both (1) a long-term, structural pattern of temple-pyramids seen as metaphors of mountains, and (2) the lens of everyday practices, in which the social lives of common people and ruins become entangled through quotidian activities. Taken together, the article highlights the dynamism of enduring structural patterns. These patterns both challenge dualistic divides of wilderness and urban settings and reveal ancient Maya urban landscapes as places of mixed temporalities.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.008
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2014
Admission routes1
Has abstractyes

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