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Record W2087881339 · doi:10.3197/096734001129342432

Frontier Foods for Late Medieval Consumers: Culture, Economy, Ecology <sup/>

2001· article· en· W2087881339 on OpenAlexaff
Richard C. Hoffmann

Bibliographic record

VenueEnvironment and History · 2001
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsYork University
Fundersnot available
KeywordsFrontierAbundance (ecology)GeographyEcologyMiddle AgesFish <Actinopterygii>EconomyBiomass (ecology)EcosystemFace (sociological concept)Natural (archaeology)EconomicsSociologySocial scienceFisheryBiologyArchaeology

Abstract

fetched live from OpenAlex

Abstract A continual western history of humans feeding beyond the bounds of natural local ecosystems goes back to Europe's high and later Middle Ages. This essay considers medieval long distance trades in grain, cattle, and preserved fish as antecedents to today's globalised movements of foodstuffs. Pulled by demand from consumers in populous and wealthy western Europe, significant amounts of plants, animals, their biomass, and their calories moved across major ecological boundaries, notably from thinly populated areas on Europe's peripheries. As today, the large cultural, economic, and ecological consequences are unevenly acknowledged. Distant zones of perceived abundance let consumers avoid changing their own cultural preferences and social practices by externalising, even forgetting, the social and environmental costs of satisfying them.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.184
Teacher spread0.155 · 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 designQualitative
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

Citations90
Published2001
Admission routes1
Has abstractyes

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