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Record W4414214352 · doi:10.1017/aaq.2025.13

Landscapes, Religion, and Social Change in Pueblo History

2025· article· en· W4414214352 on OpenAlexaboutno aff
Robert S. Weiner, Scott G. Ortman

Bibliographic record

VenueAmerican Antiquity · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsIndigenousEliteEthnographyArtifact (error)Quarter (Canadian coin)ArchitectureEthnohistorySocial changePrehistoryDocumentation

Abstract

fetched live from OpenAlex

Abstract In this article, we explore transformations and continuities in cosmology and cultural landscape structure across Pueblo history in the US Southwest. Many researchers have directly compared the archaeology of the society centered at Chaco Canyon (ca. AD 850–1140) in northwestern New Mexico with ethnographic documentation of Pueblo communities from the nineteenth and twentieth centuries. This approach makes it difficult to understand how cultural transformation played out in the intervening centuries. Here, we investigate this history by comparing Kin Nizhoni, a Chaco-era Great House community in the Red Mesa Valley, with Wiyo’owingeh, a post-Chacoan community in the Rio Grande Valley. We find that the built environments of both sites expressed similar cosmological principles, but architectural expressions of these concepts became less explicitly marked over time. We also find that this similar cosmology was mapped onto different social structures, with a focus on elite architecture in the Chaco era as opposed to communal dwellings with spatially separated shrines in later Pueblo contexts. We close by proposing a connection between the functions of Chacoan Great Houses and later Pueblo World Quarter Shrines. Overall, our findings underscore the utility of cultural landscape studies for tracing relationships between religion and society across North American Indigenous histories.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.083
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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