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Record W4407121988 · doi:10.1098/rsos.241300

Pigs, people, and proximity: a 6000-year isotopic record of pig management in Ireland

2025· article· en· W4407121988 on OpenAlexafffund
Eric Guiry, Fiona Beglane, Finbar McCormick, Eric Tourigny, Michael P. Richards

Bibliographic record

VenueRoyal Society Open Science · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsSimon Fraser UniversityTrent University
FundersSocial Sciences and Humanities Research Council of CanadaUniversity College CorkUniversity of GalwayWenner-Gren FoundationNational University of IrelandDublin City UniversityIreland Canada University Foundation
KeywordsHuman settlementPrehistoryAnimal husbandryLivestockPeriod (music)GeographyZooarchaeologyAgency (philosophy)Human animalArchaeologyRange (aeronautics)IrishEthnologyHistoryBiologyEcologySociologyAgricultureArtSocial science

Abstract

fetched live from OpenAlex

The ways that pigs interact with humans are more flexible than other livestock. This plasticity means that pig behaviour can evidence a tremendous range of cultural phenomena, some of which may not otherwise show up in the archaeological record. We explore how people and pigs interacted in Ireland over 6000 years (4000 BC-AD 1900) from the perspective of isotopic zooarchaeology, using a large sample of pigs from 40 sites. Results demonstrate continuity and dramatic change. While pig diets show an emphasis on pannage throughout much of the period, husbandry was fundamentally reconstructed in the early medieval period. Through prehistory, pigs were herded in areas distant from human settlements, whereas later they were relocated to live near people. We explore potential implications of these patterns at a range of scales, from economics, to perspectives on zoonoses, and animal agency. While syntheses of a similar scope are needed for other areas of Europe, these findings may reflect a uniquely Irish trajectory of human-animal relationships.

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)0.001
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 score0.052
Threshold uncertainty score0.322

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.001
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 head0.009
GPT teacher head0.229
Teacher spread0.221 · 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

Citations3
Published2025
Admission routes2
Has abstractyes

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