MétaCan
Menu
Back to cohort
Record W4318619845 · doi:10.1558/aff.20801

Beer, Drugs and Meat

2023· article· en· W4318619845 on OpenAlexaff
Justin Jennings, Aleksa K. Alaica, Matthew E. Biwer

Bibliographic record

VenueArchaeology of Food and Foodways · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of AlbertaRoyal Ontario Museum
Fundersnot available
KeywordsExpansionismState (computer science)PoliticsSettlement (finance)EmpireGeographyGeopoliticsEthnologyConsumption (sociology)Political scienceHistoryArchaeologySociologyLawSocial science

Abstract

fetched live from OpenAlex

Feasts were integral to pre-Columbian political economies in the Andes. The large feasts of the Inca Empire, which institutionalized asymmetrical relationships between subjects and the state, are the best known, and a point of comparison for many pre-Inca societies. It is therefore unsurprising that the feasts hosted by the Wari, an expansionist state in the central highland of Peru some 700 years earlier, are often assumed to have played a similar role. In this article, we argue that there were substantial differences between early Wari and Inca practices that reflect the different objectives of their hosts. The large feasts in Inca plazas emphasized the unbridgeable gap between ruler and subjects, while early Wari hosts strove to build interpersonal relationships between households in far more intimate affairs. To better understand the nature of Wari feasting, we discuss the acquisition, preparation, consumption and disposal of roasted camelid meat and hallucinogen-laced beer that were featured at the feasts of the Wari-affiliated settlement of Quilcapampa. The differences in feasting practices may relate to profound differences between early Wari and Inca statecraft that would narrow in Wari’s final century, as the state matured.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.437

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 head0.032
GPT teacher head0.302
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueArchaeology of Food and FoodwaysSame topicPsychedelics and Drug StudiesFrench-language works237,207