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The Pritzker Architecture Prize and its potential for developing library tourism

2024· article· en· W4403063116 on OpenAlexvenueno aff
Radoslav Hristov

Bibliographic record

VenueCanadian Journal of Information and Library Science · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Tourism and Spaces
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureTourismEngineeringComputer architectureComputer scienceArtVisual artsHistoryArchaeology

Abstract

fetched live from OpenAlex

Star architecture is becoming a popular strategy for urban solutions, and exclusive projects are being constructed to create an image and increase media attention. The term describes buildings designed by famous architects who often capitalize on their popularity for marketing purposes in tourist destinations. The visibility of these sites effectively attracts tourists and capital to specific places. It is common for landmark buildings and their leading architects to be paired with the Pritzker Architecture Prize. This paper reviews all 72 libraries designed by prize winners from the first edition in 1979 to 2023, analyzing their potential for library tourism. The research methodology includes a documentary and content analysis (internal and online desk research) of websites, newsletters, and publications. It can be concluded that these libraries have a vast collection of resources that can entice tourists, and now they are destinations for millions of visitors. On the other hand, the authority of these architects guarantees the more significant popularity of libraries as tourist destinations. However, given the financial resources needed to implement these projects, their tourism potential can mainly benefit large cities in developed countries or traditional academic centers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0030.007
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 head0.005
GPT teacher head0.221
Teacher spread0.215 · 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.

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
Published2024
Admission routes1
Has abstractyes

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