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Record W2275649980 · doi:10.1080/13574809.2015.1133230

Multiple approaches to heritage in urban regeneration: the case of City Gate, Valletta

2016· article· en· W2275649980 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Urban Design · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsCarleton University
Fundersnot available
KeywordsRegeneration (biology)Cultural heritageVariety (cybernetics)NarrativeArchitectural engineeringIndustrial heritageHistorical heritageUrban regenerationOrder (exchange)Civil engineeringEngineeringEnvironmental planningCultural heritage managementEnvironmental ethicsHistoryGeographySociologyBusinessComputer scienceArchaeologyArt

Abstract

fetched live from OpenAlex

Using heritage resources within local urban regeneration is rarely a simple matter of preserving some structures or relating some historical events and presuming that this will make some contribution to the contemporary objectives of regeneration. Buildings, spaces and historic narratives are not in themselves heritage but they can become it. This paper examines a single case seeking answers to the question, ‘how does heritage happen?’ and specifically explores the variety of ways in which built environmental forms in particular can be treated in order to use heritage to achieve contemporary regeneration objectives.

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.374

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 studies0.0000.000
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 head0.324
GPT teacher head0.239
Teacher spread0.085 · 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