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Record W1866305864 · doi:10.1007/3-7908-1727-9_10

Conquering the inner-city: Urban redevelopment and gentrification in Moscow

2006· book-chapter· en· W1866305864 on OpenAlexaff
Oleg Golubchikov, Anna Badyina

Bibliographic record

VenueContributions to economics · 2006
Typebook-chapter
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGentrificationRedevelopmentInner cityUrban regenerationGeographyCivil engineeringEnvironmental planningEngineering

Abstract

fetched live from OpenAlex

The politico-economic transformation in Moscow since the collapse of the state socialism has brought Moscow wealth and prosperity. The Moscow government's entrepreneurial strategy has facilitated that process by encouraging renovation of the inner city's housing and has privileged market forces in relation to the inner city's original residents and even in relation to the interests of this city's historic conservation institutions. While housing privatization has created the supply for the residential markets, socio-economic stratification has created differential demand and varying ability to maintain the residential units. The changes have been particularly intensive in Central Moscow, which traditionally had been both the administrative and business center and a prestigious place of residence. Introducing a housing market has set in motion demographic filtering by price, to which has begun to distribute people in space according to their economic wealth.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0030.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.256
Teacher spread0.235 · 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 designQualitative
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

Citations20
Published2006
Admission routes1
Has abstractyes

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