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Record W4283260834 · doi:10.18357/bigr32202220783

Bunker Mentalities: The Shifting Imaginaries of Albania’s Fortified Landscape

2022· article· en· W4283260834 on OpenAlexaffvenue
Frédèric Lasserre, Enkeleda Arapi, Mia M. Bennett

Bibliographic record

VenueBorders in Globalization Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicBalkans: History, Politics, Society
Canadian institutionsUniversité LavalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsBunkerEconomyCommodificationPopulationPolitical scienceSociologyGeographyArchaeologyEconomics

Abstract

fetched live from OpenAlex

Between 1967 and 1986, the Albanian government built an estimated 750,000 small and medium-sized military bunkers for defense purposes. These concrete constructions were spread across the country’s territory, with many concentrated along borders and beaches, in cities, and near key industries, strategic points, and transportation infrastructure. Long symbols of the communist regime, after it collapsed in 1991, the bunkers lost their purpose. As a result, both the narratives surrounding bunkers and their actual uses experienced significant transformations. Originally designed to control borders and instill fear in the population, bunkers have since been abandoned, destroyed, and graffitied, as might be expected. More notably, local entrepreneurs have transformed some bunkers into hotels or restaurants, while the state and non-profit organizations have turned others into commemorative sites that respectively glorify or expose the communist regime’s undertakings. Our ethnographic research into the discursive and material shifts to Albania’s fortified landscape, based on several field trips, interviews and investigations carried out between 2007 and 2017, identifies four contemporary “bunker mentalities” in Albania: indifference, derision, commodification, and commemoration.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0040.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.341
Teacher spread0.318 · 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
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueBorders in Globalization ReviewSame topicBalkans: History, Politics, SocietyFrench-language works237,207