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Record W3155669035 · doi:10.1017/laq.2021.15

Late Intermediate Period Funerary Traditions, Population Aggregation, and the Ayllu in the Sihuas Valley, Peru

2021· article· en· W3155669035 on OpenAlexaff
Justin Jennings, Willy Yépez Álvarez, Stefanie Bautista, Beth K. Scaffidi, Tiffiny A. Tung, Aleksa K. Alaica, Stephen Berquist, Luis Manuel González La Rosa, Branden Rizzuto

Bibliographic record

VenueLatin American Antiquity · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicLatin American history and culture
Canadian institutionsUniversity of TorontoRoyal Ontario Museum
Fundersnot available
KeywordsPeriod (music)GeographyPopulationArchaeologyColonial periodHistoryAncient historyEthnologyColonialismDemographySociology

Abstract

fetched live from OpenAlex

The Late Intermediate period in the south-central Andes is known for the widespread use of open sepulchres called chullpas by descent-based ayllus to claim rights to resources and express idealized notions of how society should be organized. Chullpas, however, were rarer on the coast, with the dead often buried individually in closed tombs. This article documents conditions under which these closed tombs were used at the site of Quilcapampa on the coastal plain of southern Peru, allowing an exploration into the ways that funerary traditions were employed to both reflect and generate community affiliation, ideals about sociopolitical organization, and land rights. After a long hiatus, the site was reoccupied and quickly expanded through local population aggregation and highland migrations. An ayllu organization that made ancestral claims to specific resources was poorly suited to these conditions, and the site's inhabitants instead seem to have organized themselves around the ruins of Quilcapampa's earlier occupation. In describing what happened in Quilcapampa, we highlight the need for a better understanding of the myriad ways that Andean peoples used mortuary customs to structure the lives of the living during a period of population movements and climate change.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score1.000

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 studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.223
Teacher spread0.208 · 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.

Study designQualitative
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

Citations8
Published2021
Admission routes1
Has abstractyes

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