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Record W2153221284 · doi:10.3905/jpe.2007.682348

Lead Trump or Risk Losing? <i>A Comparison of Bidding Procedures for the Acquisition of a Business in Canadian and U.S. Restructuring Proceedings</i>

2007· article· en· W2153221284 on OpenAlex
Steven J. Weisz, Lindsay Bunt

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Private Equity · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicLaw, Economics, and Judicial Systems
Canadian institutionsnot available
Fundersnot available
KeywordsDebtorRestructuringBiddingBusinessFinancePortfolioBankruptcyCreditorMarketingDebt

Abstract

fetched live from OpenAlex

The goal for any debtor selling business assets in restructuring proceedings is to maximize realization. The process by which the assets are sold certainly contributes to the debtor9s success in achieving this goal. In Canada, sales processes have generally been based on a close-bid system in which a winning bid is chosen privately and then recommended for court approval. In the US, a two-step process is used in which a “stalking horse” bid is accepted on the condition that it will be later subject to an open judicial auction. Once the auction is complete, the debtor will seek court approval of a sale to the winning bidder. In this paper, we examine which process best achieves the debtor9s goal of maximum realization for its assets. <b>TOPICS:</b>Private equity, developed, financial crises and financial market history, portfolio construction

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.050
GPT teacher head0.283
Teacher spread0.233 · 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