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Land Demarcation in Ancient Rome

2020· book-chapter· en· W3044812880 on OpenAlexaboutno aff
Gary D. Libecap, Dean Lueck

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicClassical Antiquity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpireExpansiveGeographyState (computer science)Roman EmpireAncient historyOrder (exchange)ArchaeologyHistoryBusinessComputer science

Abstract

fetched live from OpenAlex

Ancient Rome was an expansive and wealthy empire that created a trading network that relied on common language(s), law, money, and a system of measurement. An important component of this network was the rectangular system (RS) of land demarcation known as centuriation, which was the forerunner of similar systems adopted in the United States and Canada and in other parts of the British Empire in the eighteenth and nineteenth centuries. This purposefully implemented demarcation system persists to the present and can be found in the landscape throughout the territories of the former Empire, especially in Italy and North Africa. It was typical as Rome expanded its territories to implement the RS system before new lands were settled by Romans. There was considerable variation in land demarcation patterns across the Empire. This chapter examines the determinants of centuriation by describing a model in which the state chooses between adopting RS to demarcate new lands or to utilize existing demarcation. The chapter examines data on centuriated areas and accounts from archeologists and classics scholars to examine the economic structure of Roman centuriation. The chapter generally finds that centuriation was adopted in flatter, more fertile lands, and later in time as survey techniques improved and administrative structures were expanded. The chapter also finds that alignment tended to be perpendicular to rivers and streams in order to minimize demarcation costs and to facilitate a network of canals for drainage. Finally, the chapter provides conjectures about the impact on centuriation on development and growth within the Empire.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.995
Threshold uncertainty score0.734

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 studies0.0000.000
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 head0.044
GPT teacher head0.247
Teacher spread0.204 · 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
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

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