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Record W4415815031 · doi:10.1080/02723638.2025.2575758

Contemporary hazard and health discourse in urban renewal: a critical examination of smart, sustainable, earthquake and pandemic-proof imaginaries driving dispossession in Tirana, Albania

2025· article· en· W4415815031 on OpenAlexaff
Ervin Goci, Suzanne Harris-Brandts

Bibliographic record

VenueUrban Geography · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare Facilities Design and Sustainability
Canadian institutionsCarleton University
Fundersnot available
KeywordsHazardPrecarityCritical discourse analysisNeoliberalism (international relations)Urban planning

Abstract

fetched live from OpenAlex

Amidst a global surge in urban development foregrounding smart, sustainable, and now pandemic-proof design, new forms of longstanding hazard and health discourse are being deployed to justify dispossession, particularly in self-built districts. Looking at a case in Tirana, Albania, we examine how this discourse is being contemporized and paired with diverse digital media as it overlaps within a single project – the Tirana Riverside Project. As expressions of authoritative knowledge, architectural visualizations, social media posts, state-backed news broadcasts, and international design blogs work to validate this underlying ideology driving demolition. Such imagery and discourse, we contend, thus need to be read as artifacts of power that entrench government authority while substantiating mass dispossession. We argue that these processes are not only about the real estate profits demolition-based urban renewal generates but also – in Albania’s flawed democratic context – their ability to support the ruling elite. Using content analysis, we identify four hazard and health imaginaries overlapping within the project: 1) pandemic-proof design; 2) design for seismic emergencies; 3) zero-emission sustainable design; and 4) smart city technologies. We show how these imaginaries join longer traditions of normative discourse around hazard and health in urban renewal yet scrutinize their distinct contemporized and localized expressions.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.050
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
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 head0.022
GPT teacher head0.343
Teacher spread0.321 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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