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Record W3023644403

Think Global, invest responsible: why the private equity industry goes green

2012· preprint· en· W3023644403 on OpenAlexaff
Patricia Crifo, Vanina Forget

Bibliographic record

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2012
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsCenter for Interuniversity Research and Analysis on Organizations
Fundersnot available
KeywordsPrivate equityClub dealMainstreamPrivate equity firmPrivate equity fundBusinessPrivate equity secondary marketShareholderCorporate governancePrivate investment in public equityEquity (law)FinanceEquity riskAlternative investmentEquity capital marketsInvestment (military)Politics
DOInot available

Abstract

fetched live from OpenAlex

The growth of socially responsible investment on public financial markets has drawn considerable academic attention over the last decade. Discarding from previous literature, this paper sets up to analyze the Private Equity channel, which is shown to have the potentiality to foster sustainable practices in unlisted companies. The fast integration of the Environmental, Social and Governance issues by mainstream Private Equity investors is unveiled and appears to have benefited from the maturation of socially responsible investment on public financial markets and the impetus of large conventional actors. Hypothesis on the characteristics and drivers of this movement are proposed and tested on a unique database covering the French Private Equity industry in 2011. Empirical findings support that Private Equity responsiblen investing is characterized by shareholder activism and strategically driven by a need for new value creation sources, increased risk management and differentiation. In particular, results show that independent funds, which need to attract investors, are more likely than captive funds to develop responsible practices. Evolution of the movement and future research paths are proposed.

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0040.012
Research integrity0.0010.002
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 head0.035
GPT teacher head0.257
Teacher spread0.222 · 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 designTheoretical or conceptual
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

Citations1
Published2012
Admission routes1
Has abstractyes

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