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SMART CITIES AND HERITAGE CONSERVATION: DEVELOPING A SMARTHERITAGE AGENDA FOR SUSTAINABLE INCLUSIVE COMMUNITIES

2017· article· en· W2769147247 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Architectural Research Archnet-IJAR · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsCrowdsourcingInformation and Communications TechnologyCitizen journalismValuation (finance)Cultural heritageCorporate governanceEnvironmental planningCultural heritage managementSustainabilityEnvironmental resource managementBusinessPolitical scienceKnowledge managementGeographyComputer scienceEconomics

Abstract

fetched live from OpenAlex

This paper discusses the potential of current advancements in Information Communication Technologies (ICT) for cultural heritage preservation, valorization and management within contemporary cities. The paper highlights the potential of virtual environments to assess the impacts of heritage policies on urban development. It does so by discussing the implications of virtual globes and crowdsourcing to support the participatory valuation and management of cultural heritage assets. To this purpose, a review of available valuation techniques is here presented together with a discussion on how these techniques might be coupled with ICT tools to promote inclusive governance.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.104
GPT teacher head0.395
Teacher spread0.291 · 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