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Record W4408672597 · doi:10.1080/08865655.2025.2457634

A Divine Inspiration for Border Studies; Conceptually Excavating the Polydivine Roman Border Landscape of Terminus, Janus, Mercurius, Trivia and Pluto

2025· article· en· W4408672597 on OpenAlexvenueno aff
Paschalina T. Garidou, Henk van Houtum, Saskia Stevens, Luuk Winkelmolen

Bibliographic record

VenueJournal of Borderlands Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsJanusPlutoAstrobiologyArtAestheticsPhysicsNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

What can we learn from the Romans regarding the understanding of borders? For various contemporary populist politicians, Roman history teaches us the need for harsh and strict borders, to prevent the invasion of “barbarians” and the “fall” of the European Union. To assess their claim, we trace back the Romans’ own source of inspiration for their territoriality and border ideology: the Roman border gods. Using this conceptual archaeological lens we critically counter the populist reductionism and selective history shopping, and explore the potential of the diverse Roman gods to further enrich the contemporary border studies academic debate. We conceptually excavate the polydivine dialogue among significant Roman border-related gods: Terminus, whose representation of border fixity inspires the dominant politicized debate on ultra-securitised borders, along with Janus, Mercury, Trivia, and Pluto, each offering diverse perspectives on borders. Diving into the divine inspiration of the Roman border gods, it becomes evident that we can learn a lot from the Romans indeed – and far more than the misleading and selective interpretations presented by populist politicians.

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)0.002
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.040
GPT teacher head0.425
Teacher spread0.385 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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