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Record W3154484545

Social Value Toolkit for Architecture: Guidance on evaluating the social value impact on people and communities delivered by a project

2020· article· en· W3154484545 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

VenueExplore Bristol Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsValue (mathematics)ArchitectureSocial impactSociologyComputer sciencePublic relationsPolitical scienceGeographyPopulation
DOInot available

Abstract

fetched live from OpenAlex

The Social Value Toolkit for Architecture has been developed to make it simple to evaluate and demonstrate the social impact of design on people and communities. <br/>Social value outcomes are increasingly being considered necessary benefits in public and private procurement through quality scores of bids and tenders. To provide evidence that meets these key performance targets and metrics, practices need to demonstrate value quantitatively and this toolkit provides a post occupancy evaluation survey and methodology for reporting social value as a financial return on investment.<br/>The Social Value Toolkit was developed through a research project led by the University of Reading and included representatives from the RIBA and research leaders in architectural practice. Download the guidance below to hear from some of these researchers on how their practice is building social value into their projects and design processes.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.312
GPT teacher head0.466
Teacher spread0.154 · 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