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Record W7027532342

Conceptual Approaches to Environmental Quality and Livability in Smaller Cities

2019· article· en· W7027532342 on OpenAlexaboutno aff

Bibliographic record

VenueRAF (Faculty of Architecture, University of Belgrade) · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Immunotherapy and Biomarkers
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationQuality (philosophy)Context (archaeology)Government (linguistics)Gloom
DOInot available

Abstract

fetched live from OpenAlex

Livable city means a city that can effectively meet the needs of its population regardless of age, gender, social situation or level of education. Many official rankings publish annually a list of the most suitable urban places for life, evaluated according to number of indicators including infrastructure and public transport, urban design and architecture, health and education system, safety and crime, climate, socio-economic and environmental problems, connections to nature, and others. Top 10 places ranked regularly are Melbourne, Vienna, Vancouver, Toronto, Calgary, Adelaide, Sydney, Helsinki, Perth, Auckland . It is interesting to note that the geographic location and climate of these livable favorites is not ideal; the bad weather, snow, darkness and cold last for at least 6 months of the year. So which values prevail in the selection of people for the quality of life? The issue of livability or as well the quality of life in the context of urban design and environmental quality and sustainability is of much interest of interdisciplinar academic research, more frequent since 1960ties. Street negation by modernists and the functionalist ideals of hygienic and lighted settlements supported the creation of impersonal high-rise buildings coupled by roads without active public spaces. As a reflection on modenistic principles in architecture and urban design and continued growth and preference for automobiles the new theoretical and practical works were born, such as Jane Jacobs voice calling for the cities humanization of or Jan Gehl´s theoretical approach and practical design for many great cities, which can be characterized as urbanistic humanism and the return of the city to its real users. Urban design is all about the human dimensions. Not about cars, industry or business. The quality of life has to be on the first place, followed up by space and buildings – other way round it does not work. If people perceive positively the city for their life, everything else will come gradually (Gehl, 2014). The quality of urban life is primarily concerned with the qualitative aspects of the city's life as a whole. Simply it is expressed as "friendly relations" of its inhabitants and visitors to the city and to the degree of infrustructural and urban amenities (Bašová, 2014). Attempts are now being made to humanize cities, to increase their livability, to improve the public space for people and this way encouraging them to walk and cycle. Open public spaces are only attractive for users if there is a certain concentration of people. When an osmosis between open spaces and the city occurs – it is an osmosis of the human presence in the streets with the human presence in public spaces (Djukic et al.,2018). Factors such as the presence and quality of walkways, safety, isolation from disturbing traffic influences, distances, accessibility, creation of a mixed-function and attractive environment affect user preferences and ultimately affect health, environmental and economic benefits.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.004
Science and technology studies0.0060.048
Scholarly communication0.0110.014
Open science0.0030.008
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.076
GPT teacher head0.247
Teacher spread0.171 · 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 designTheoretical or conceptual
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

Citations1
Published2019
Admission routes1
Has abstractyes

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