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Record W4318659604 · doi:10.1558/aff.21427

Editors’ Introduction

2022· article· en· W4318659604 on OpenAlexaff
Erica Rowan, Shanti Morell‐Hart, Shinya Shoda

Bibliographic record

VenueArchaeology of Food and Foodways · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

Food is mundane, a necessity for basic human survival.Yet it is also deeply imbued with cultural, economic, spiritual and political significance.As both quotidian sustenance and social cornerstone, food has always played a central role in human lifeways.Alongside rich depictions of culinary arts in ancient paintings, and lush descriptions in ancient writings, food and its associated materials have left numerous traces in the archaeological record.Once simply considered in caloric terms for subsistence modeling, or sometimes as curiosity in the occasional funerary setting, the study of past foodways has grown exponentially in recent decades to encompass a number of social and environmental topics.Decades of archaeological studies have shed new light on social dynamics as well as ethnoecological issues in the human past, using traces of foodways scattered across media.Ancient food studies makes use of virtually all subdisciplines of archaeology, including ceramic and residue analysis, archaeobotany, zooarchaeology, isotope analysis, features and activity areas, sensory archaeology, and ethnographic research.Significant advances in environmental archaeology and archaeological science have enabled us to view and study human relationships with food in more depth and detail than ever before.The time has come to devote a journal entirely to these topics, to capture the wealth of food studies and facilitate discussion between food scholars.Archaeology of Food and Foodways is an interdisciplinary, peer-reviewed journal that welcomes original research on any aspects of the archaeology of food.The journal aims to be a home for archaeologists who, while specialists in particular regions, cultures or artifact types, are also broadly-informed and make use of other forms of material culture.By having a journal focused on the archaeology of food, rather than food more generally, we have created a space where scholars can discuss their work and findings in considerable depth and detail.This is a space where the hard sciences, soft sciences and humanities can be presented side by side and easily enter into dialogue with one another.Since food cuts across cultures and time

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
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 studies0.0000.001
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 head0.008
GPT teacher head0.174
Teacher spread0.166 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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