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Renovation of residential areas for benefit of builders, state and citizens

2019· article· en· W2990722691 on OpenAlexaboutno aff
Ольга Грушина, Ирина Торгашина

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsDemolitionBusinessResidenceStock (firearms)Quarter (Canadian coin)Profit (economics)Modernization theoryOrder (exchange)Housing industryArchitectural engineeringEnvironmental planningFinanceEngineeringCivil engineeringEconomic growthGeographyEconomics

Abstract

fetched live from OpenAlex

Abstract The paper deals with the problem of residential housing renovation projects for benefit of builders, citizens and state. The numerous interpretations of the “renovation” term we understand here as a complete renovation of the housing stock, i.e. demolition of old buildings and construction of new ones in contrast to their reconstruction and modernization. In other words, the renovation is considered as an urgent city-planning challenge involving changes in the field of territorial planning. On the example of the classic “Khrushchev” quarter of Irkutsk city, the authors propose a pilot renovation project with the distribution of roles and expenditures of all participants. The analysis conducted allows drawing a conclusion that renovation will be beneficial to the builder only if budget funds are invested in these projects in order to compensate the costs related to temporary resettlement of citizens from demolished dwellings. Another prerequisite is the governmental repurchase of apartments intended for resettlement of citizens from demolished housing at the prices not lower than those set by the authorities in the region. Citizens are ready to support renovation projects in case of their returning to their former place of residence in conditions improved from the point of view of the living environment comfort. To ensure the profit of the builder, the living area of the newly commissioned housing should exceed the area of the demolished housing by no less than one and a half times, provided that cheap technologies of modern prefabricated housing are used.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.442

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 science0.0000.000
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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2019
Admission routes1
Has abstractyes

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