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Record W2981757805 · doi:10.3138/mous.16.s2-6

Millers and Millwrights in Antiquity and the Early Middle Ages

2019· article· en· W2981757805 on OpenAlexvenueno aff
Örjan Wikander

Bibliographic record

VenueMouseion Journal of the Classical Association of Canada · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicAncient Mediterranean Archaeology and History
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusTerminologyScholarshipMiddle AgesPresentation (obstetrics)HistorySpace (punctuation)Order (exchange)Demographic economicsSociologySocial sciencePolitical scienceDemographyAncient historyEconomicsLawLinguisticsPhilosophyPopulationMedicine

Abstract

fetched live from OpenAlex

The study of early watermills has, from its very beginning, concentrated on two issues: their diffusion (in time and space) and their technical construction. Very little interest has been devoted to the persons who built and managed them—the millwrights and the millers. This tendency has been even more manifest from the 1980s onward, when interest has focused more and more on the increasing number of archaeological finds. The written evidence, our almost sole source for people connected with the mills, plays a quite insignificant part in modern scholarship. This short article does not aim at far-reaching conclusions concerning the socioeconomic conditions of the two professions involved. Its main purpose is to show the extent of the evidence actually at hand. The varied nature of this evidence, as well as the uncertain authenticity of parts of it, complicates the study. After a short presentation of the terminology, I start my investigation by presenting the millers according to the three basic socioeconomic areas within which they were working, and end up with a discussion of the millwrights, in order to show how the two occupations were at least partly related.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.682

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 studies0.0000.000
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 head0.011
GPT teacher head0.174
Teacher spread0.163 · 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 designNot applicable
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
Published2019
Admission routes1
Has abstractyes

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Same venueMouseion Journal of the Classical Association of CanadaSame topicAncient Mediterranean Archaeology and HistoryFrench-language works237,207