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Record W7038250770

Government Interventions Have a Limited Impact on Chicago Area Foreclosure Activity in 2009

2010· report· en· W7038250770 on OpenAlexaboutno aff

Bibliographic record

VenueIssue Lab (Candid) · 2010
Typereport
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
Fundersnot available
KeywordsForeclosureQuarter (Canadian coin)Government (linguistics)County governmentFinancial crisis
DOInot available

Abstract

fetched live from OpenAlex

Analysis of 2009 data on new foreclosure filings and completed foreclosure auctions in the Chicago region shows: New foreclosure filings in the Chicago six-county region increased to over 70,000 in 2009, up 21 percent from 2008. Areas in the region with the most rapid rate of growth in foreclosure filings include North and Northwest Suburban Cook County and Kane County. Each area saw increases in new filings of between 48.5 and 40 percent from 2008. In the City of Chicago, Lincoln Park, Uptown, and East Side saw the largest increases. Lincoln Park saw an increase of 103.2 percent while Uptown and East Side saw increases of almost 75 percent from 2008. Parts of the region that for many years have been hard hit by the foreclosure crisis saw declines in new foreclosure filing activity in 2009. Foreclosure filings in South Suburban Cook County declined by 6.5 percent from 2008. In the City of Chicago, 25 community areas saw year over year declines. Most notably Woodlawn, West Pullman, and Englewood saw declines between 25.9 and 23.8 percent from 2008. The fourth quarter of 2009 had the highest level of foreclosure filing activity for any quarter since the foreclosure crisis began in 2006 with 24,053 new filings. South Cook County continues to have the highest level of foreclosure filings per property at 42.8 filings per 1,000 mortgageable properties, but the rest of the region is catching up. In 2009, the six-county area averaged 30.8 filings per 1,000 mortgageable properties. In the City of Chicago, new foreclosure filings on condominium units continue to increase at a dramatic rate of 36.8 percent from 2008, compared to an 8.6 percent increase in filings on single-family homes. Foreclosure filings on condo units now make up 24 percent of all foreclosure filings in the city. Changes in completed foreclosure auction activity between 2008 and 2009 varied dramatically across the region. For example, Cook County saw a nearly nine percent decrease in completed foreclosure auction between 2008 and 2009, while Kane County saw a 57.2 percent increase in completed auctions over the same period. While the total number of completed foreclosure auctions remained fairly stable between 2008 and 2009, the number of properties purchased at auction by outside buyers increased by nearly 46 percent from 2008. South Suburban Cook County and the City of Chicago continue to have the highest concentrations of REO foreclosure auctions per property with 17.2 and 15.8 auctions per 1,000 mortgageable properties respectively.Despite key federal, state, and local interventions developed to limit the impact of foreclosures on the region's homeowners and communities, the foreclosure problem in the Chicago region continued to grow in 2009. The following analysis details the growth of new foreclosure filing activity in the region as well as shifts in the geographic patterns of new foreclosure filings. Additionally, the report looks at changes in the levels of completed foreclosure auctions in the region. The report also includes detailed appendices with data for City of Chicago community areas and municipalities in the Chicago six-county region. Finally, this analysis includes data for DeKalb, Kendall, and Winnebago Counties.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1620.001

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 head0.051
GPT teacher head0.325
Teacher spread0.274 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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