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Record W4387720705 · doi:10.22530/ayc.2023.23.635

La diversidad y los usos mixtos en los entornos culturales y creativos como impulsores de la participación ciudadana y la sostenibilidad: análisis del St. George’s Cultural Quarter (Leicester, Reino Unido)

2023· article· es· W4387720705 on OpenAlexaboutno aff
Jennifer García Carrizo

Bibliographic record

VenueArte y Ciudad · 2023
Typearticle
Languagees
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsCreative cityQuarter (Canadian coin)Creative CitiesSociologyPhoenixGeorge (robot)Promotion (chess)HumanitiesGeographyCreativityPolitical scienceArtMetropolitan areaArt historyArchaeology

Abstract

fetched live from OpenAlex

Cultural and creative urban areas are fundamental in our cities for cultural development and the promotion of creativity in the city. This research aims to examine the importance of diversity and mixed uses in these areas, focusing on the case study of the St. George’s Cultural Quarter in Leicester, United Kingdom. It highlights how the combination of different cultural and creative activities, together with the diversity of actors involved in them, contributes to the promotion of citizen participation and the revitalisation of an area. Through a detailed analysis of this case study, successful strategies to promote social cohesion and sustainability in cultural and creative urban areas are identified. To do this, this research presents different activities developed by spaces in the St. George’s Cultural Quarter such as the LCB Depot, Leicester Print Workshop, the Curve Theatre, the Phoenix Digital Media Center and the Chutney Ivy.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0020.005
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.335
Teacher spread0.309 · 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 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
Published2023
Admission routes1
Has abstractyes

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