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Record W2774123902 · doi:10.15304/rge.26.2.4449

SMART CITIES, SMART TOURISM? THE CASE OF THE CITY OF PORTO

2017· article· en· W2774123902 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

VenueRevista Galega de Economía · 2017
Typearticle
Languageen
FieldEngineering
TopicSmart Cities and Technologies
Canadian institutionsChemistry Industry Association of Canada
Fundersnot available
KeywordsSmart cityScope (computer science)AppealTourismDestinationsCreativityCitizenshipBusinessRegional scienceMarketingPolitical scienceGeographyEngineeringComputer scienceInternet of ThingsPolitics

Abstract

fetched live from OpenAlex

The so-called Smart Cities have been playing an important role in the academic literatureas well as in the agenda of public policies. With the forward thinking of “creating” newurban development models, the cities intend to strategically positioning themselves and atthe same time develop cooperation networks. Frequently using the Information andCommunication Technologies (while as a means to an end and not as an end itself), thecities try to assure a greater economic competitiveness, the environmental sustainabilityand the reinforcement of citizenship (calling out to people to participate, in the scope of aninclusive logic and in an appeal to creativity and social responsibility).Even the 2020European strategy promotes this development.The geographic scope of the study islimited to the city of Porto. This is justified by the fact that, in 2015, Porto was one the fiveEuropean cities selected to participate in the GrowSmarter (model of organization of citiesof the future), an ambitious project with the objective of making Europe more sustainableand environmentally intelligent.Besides that, the Portuguese Smart Cities Index, 2016, points out the city of Oporto as thePortuguese city with better results in what concerns the main vectors of intelligence(policy, strategies and projects implemented, edification, mobility, energy and smartservices).At the same time, in the international press, the city of Porto appears as areference for its architectural wealth and as one of the more indicated Europeandestinations for one who would like to enjoy quality holidays at a reasonable price.That isperhaps why Shermans Travel presents Porto as one of the top 10 destinations forintelligent tourists. The purpose of the present study is to understand if the emergence ofsmart cities can be in some way connected to the appearance of smart tourism. For such apurpose, we will study the city of Porto and a survey will be conducted among the touristsof the city.This article compiles some of the first results of the study, referring to the datacollected during the months of August and September of 2017, and intends mainly to setout some hypotheses about the motivation for the choice of a tourist destination, that willbe developed in future works.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.446
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.217
Teacher spread0.201 · 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