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Record W2741717884 · doi:10.1016/j.foar.2017.06.001

Successes and failures of participation-in-design: Cases from Old Havana, Cuba

2017· article· en· W2741717884 on OpenAlexafffund
Arturo Valladares

Bibliographic record

VenueFrontiers of Architectural Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsMcGill University
FundersFonds de Recherche du Québec-Société et Culture
KeywordsArchitectureWork (physics)Citizen journalismPolitical scienceEconomic growthPublic administrationPublic relationsEngineeringGeographyLawEconomics

Abstract

fetched live from OpenAlex

Following the fall of the Soviet Union, Cuba faced a crisis that forced it to change its housing approach. Self-help building programs began to supplant the construction of mass standardized housing estates. The Community Architect Program was developed to provide design advice to self-help builders, and it expanded exponentially within a decade. By the year 2000, all municipalities across Cuba had their own Community Architect Office. While the approach of the Community Architect Program has been hailed a breakthrough in the fields of planning and architecture, the particular case of Old Havana suggests that several obstacles prevent residents from benefiting from its services. The author identifies the strengths and limitations of the approach by looking at two home renovation projects in Old Havana and the perceptions of low-income residents on the work done by community architects. This research indicates that participatory design methods should be complemented by community-based initiatives that address other aspects of the housing development process, such as access to materials, construction, and construction management.

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)0.006
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.009
Scholarly communication0.0050.002
Open science0.0030.007
Research integrity0.0020.002
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 head0.144
GPT teacher head0.432
Teacher spread0.288 · 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 designQualitative
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

Citations7
Published2017
Admission routes2
Has abstractyes

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