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Record W6999283097

Chicago film studio forced to return state grant

2015· other· en· W6999283097 on OpenAlexaboutno aff

Bibliographic record

VenueInternet Archive (Internet Archive) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsStudioState (computer science)Administration (probate law)GovernorReal estateEstateBox office
DOInot available

Abstract

fetched live from OpenAlex

Cinespace Chicago Film Studios's given back $10 MILLION plus to the state after a Chicago Sun-Times investigation prompted Gov. Bruce Rauner to demand repayment of a state-issued grant The studio where Chicago Fire, Empire, and other TV shows and movies're filmed has found itself in a controversy over state money and real estate deals involved in the expansion of its studios. Cinespace Chicago Film Studios bills itself as the largest film studio complex east of Los Angeles, it's expanded in North Lawndale along the east side of Douglas Park, including taking over and renovating the former Ryerson Steel plant. But last weekend, an investigation by the Sun-Times found the studio'd received millions of dollars to buy land that wasn't even for sale as it looks to expand by buying up properties along Western Avenue. One of those grants, for ten million dollars, was issued by former-Governor Pat Quinn just three weeks before he left office. On Monday, Governor Bruce Rauner ordered Cinespace to give back the grant, his office says its very concerned about the lack of supporting documentation and says the Quinn administration failed to abide by the normal rules for issuing grants. Cinespace'd gotten more than 17 million in grants from Quinn's administration before the final grant, which is the only one that's being returned.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.145
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0050.005
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0180.087

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 head0.265
Teacher spread0.244 · 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
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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