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Record W4389454676 · doi:10.1080/14614103.2023.2282866

Isotopic Insights into Livestock Production in Roman Italy: Diet, Seasonality, and Mobility on an Imperial Estate

2023· article· en· W4389454676 on OpenAlexaff
Angela Trentacoste, Michael MacKinnon, Christopher Day, Petrus le Roux, Michael Buckley, Myles McCallum, Maureen Carroll

Bibliographic record

VenueEnvironmental Archaeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsSaint Mary's UniversitySt. Mary's UniversityUniversity of Winnipeg
FundersEngineering and Physical Sciences Research CouncilRust Family FoundationAlexander von Humboldt-Stiftung
KeywordsHerdingAgricultureFodderLivestockGeographyIsotope analysisEconomyNatural resource economicsArchaeologyEcologyEconomicsBiologyForestry

Abstract

fetched live from OpenAlex

Agriculture is the most important intersection between farming communities and the natural world, with major implications for land exploitation and labour organisation. In Italy, at the heart of the Roman Empire, understanding of agriculture remains heavily dependent on ancient sources, which are unable to provide a regional or diachronic view of practices across the socio-economic spectrum. In order to gain insight into agricultural economies in Roman Italy and their social and environmental implications, this article reconstructs agro-pastoral strategies at an imperial estate in southern Italy through a multi-isotope investigation of livestock bone collagen and tooth enamel. Analysis of carbon, nitrogen, oxygen and strontium isotopes (δ13C, δ15N, δ18O, 87Sr/86Sr) are combined to evaluate animal management and mobility at Vagnari vicus and the villa of San Felice in the Basentello Valley. Results reveal taxon-specific herding strategies with the potential for significant inputs from legume forage/fodder and/or natural environments. Caprine herding did not appear to include long-distance transhumance. This analysis moves past previous text-based generalisations to provide a new and nuanced perspective on animal production in rural southern Italy and its economic and environmental implications.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.697

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 studies0.0000.002
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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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