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Record W4411454762 · doi:10.1080/14650045.2025.2514754

Geopolitics and Memorialisation of Borders

2025· article· en· W4411454762 on OpenAlexaff
Victor Konrad, Paul B. Richardson, Eeva‐Kaisa Prokkola, Juha Ridanpää, Mirza Zulfiqur Rahman, Karina Horsti, Inocent Moyo, Jussi P. Laine, María Lois, Dorte Jagetić Andersen, Dallen J. Timothy, Marek Więckowski, Edward Boyle

Bibliographic record

VenueGeopolitics · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsCarleton University
Fundersnot available
KeywordsGeopoliticsPolitical sciencePoliticsLaw

Abstract

fetched live from OpenAlex

Geopolitics pervades memorialisation of borders worldwide. Border heritage sites commonly form powerful geopolitical bordering by creating myths of division and difference to serve the nation-state, and secure hegemonic narratives. Attention to multiplicity and polyphony of border memorialisation voices reveals coincidence and collision of memories and spatial orders to form resistance to the illusionary hegemonic border. Multiple temporalities may accrue in different settings, and borders of memory occur where different understandings and ideas of national heritage sites or everyday border memorialisations meet. The memoryscapes shaped and enabled in processes of heritage making extend beyond time-bound renditions of linearity to open a wider conversation around the politics of border heritage, approach border memorialisation as spaces of encounter, possibility and hope and confront the touristic fascination and engagement with dark border heritage. In this Geopolitical Forum, 13 scholars of border heritage studies explore the global dimensions of border memorialisation and debate its impact.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.021
Scholarly communication0.0100.007
Open science0.0010.012
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.394
Teacher spread0.384 · 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 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

Citations6
Published2025
Admission routes1
Has abstractyes

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