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Record W2150040357 · doi:10.1558/jmea.2006.19.1.45

Networks, Agent-Based Models and the Antonine Itineraries

2006· article· en· W2150040357 on OpenAlexaff
Shawn Graham

Bibliographic record

VenueJournal of Mediterranean Archaeology · 2006
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsContext (archaeology)Space (punctuation)Perspective (graphical)Point (geometry)Position (finance)ArchaeologyHistoryGeographyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This paper presents a way of looking at Roman space from a Roman perspective, and suggests ways in which this point of view might open up new approaches in Roman archaeology. It turns on one conception of Roman space in particular, preserved for us in the Antonine Itineraries. Working from a position that considers the context of the itineraries as movement-through-space, this paper presents an investigation using social network analysis and agent-based simulation to re-animate the itineraries. The itineraries for Iberia, Gaul, Italy, and Britain are considered. The results of the social network analysis suggest structural differences in the way that the itineraries presented space to the reader/traveler. The results of the simulation of information diffusion through these regions following the routes in the itineraries suggest ways that this conception of space affected the cultural and material development of these regions. Suggestions for extending the basic model for more complicated archaeological analyses are presented.

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 score0.192
Threshold uncertainty score0.421

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 science0.0000.000
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 head0.067
GPT teacher head0.332
Teacher spread0.265 · 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

Citations99
Published2006
Admission routes1
Has abstractyes

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