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Record W2161638033 · doi:10.1002/jcaf.20654

M&A update

2010· article· en· W2161638033 on OpenAlexaboutno aff
Carol M. Sánchez, Christina D. Seeber, Stephen R. Goldberg

Bibliographic record

VenueJournal of Corporate Accounting & Finance · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
Fundersnot available
KeywordsCashQuarter (Canadian coin)Mergers and acquisitionsEconomicsMonetary economicsBusinessFinance

Abstract

fetched live from OpenAlex

Abstract Most of 2009 was slow for mergers and acquisitions (M&As), due to financial turmoil and economic uncertainty that carried over from late 2008. But the deal market rebounded in the fourth quarter of 2009, and 2010 appears to be much better for M&As than 2009. Yet while the global economy shows signs of recovery, and many buyers and sellers are flush with cash, M&A activity may begin slowly in the United States in 2011‐due to uncertainty about the business outlook and potential tax changes. How healthy is current deal making? And what is the short‐ and long‐term outlook for M&As?. © 2011 Wiley Periodicals, Inc.

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.005
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0490.037

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 head0.027
GPT teacher head0.229
Teacher spread0.202 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations4
Published2010
Admission routes1
Has abstractyes

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