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Record W7049053827

Negotiating the Mega-Rebuilding Deal at the World Trade: Adjacent Property Owners

2008· article· en· W7049053827 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicCrystallography and Radiation Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsWorld trade centerCenter (category theory)NegotiationProperty (philosophy)World tradeNew england
DOInot available

Abstract

fetched live from OpenAlex

I will be very brief because I am a peripheral participant in this meeting. The company with which I am connected, Brookfield, owns property near the site. We were the third highest bidder to take over the World Trade Center in a deal that was completed in 2001. If our bid had been slightly higher and we had won the contract, then my experience would have been different. However, as it stands, I am peripheral participant. My primary connection is with Alex Garvin, my college classmate and friend for almost fifty years, and Meredith Kane, one of my favorite students. I have a number of favorite students, but she is on that list.\nBrookfield, a large Canadian company, owns One Liberty Plaza, a building next door to the World Trade Center site. The law firm of Cleary Gottlieb Steen & Hamilton has its office in that building.However, Brookfield also owns the four World Financial Center buildings, which were designed by Cesar Pelli and are representative of the financial center buildings that are constructed today. At the time the World Trade Center was attacked, Merrill Lynch, Lehman Brothers, and the Wall Street Journal were in those buildings. This is Wall Street property; therefore, we bid to become the holder of the ninety-nine year interest in the World Trade Center. However, Vornado and Mr. Silverstein bid more. As a result, we had been sitting there on the edge. Then the events of September 11th occurred resulting in substantial damage to our buildings as well as to the World Trade Center.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.229
Teacher spread0.214 · 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.

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
Published2008
Admission routes1
Has abstractyes

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