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Record W4411137978 · doi:10.1016/j.jaa.2025.101707

Materiality of forager food insecurity in the archaeological record: A case study from the central Canadian Boreal Forest, ∼1100–1300 CE

2025· article· en· W4411137978 on OpenAlexafffundabout
Matt Boyd

Bibliographic record

VenueJournal of Anthropological Archaeology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsLakehead University
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaLakehead University
KeywordsMateriality (auditing)ArchaeologyTaigaBorealGeographyArchaeological recordFood insecurityHistoryForestryArtAgricultureAestheticsFood security

Abstract

fetched live from OpenAlex

• Examines the connection between food insecurity and forager material culture. • Abrupt warming 800 years ago coincided with stylistic changes in pottery in the central Boreal Forest. • Pottery was used as a container to cook aquatic foods and as a feasting object. • Stylistic changes record the disruption of cooperative aquatic food harvesting. • Highlights the value of archaeology in northern food security studies. Food insecurity is a highly disruptive force at the individual and group levels, particularly when scarce resources are culturally important. Due to the close connection between food and material culture, periods of cultural food insecurity in the past may be associated with changes in the materiality (the physical and relational manifestations of the preparation, presentation, and consumption) of these foods. In the central Canadian Boreal Forest, pottery was traditionally used to cook aquatic foods as evidenced by wild rice (manoomin, Zizania spp.) microbotanical remains in carbonized food residues on cooking pots. This paper explores the connection between periods of aquatic ecosystem instability driven by climate change and the disruption of material and social traditions linked to wild rice consumption and cooperative harvesting. This connection provides an alternative explanation for sudden stylistic transformations that occurred in pottery throughout this region approximately 800 years ago.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0100.003
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
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 head0.022
GPT teacher head0.257
Teacher spread0.235 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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