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Record W2924161261 · doi:10.3905/jpe.2019.22.2.009

Mature and Not Mature Enough: <i>Comparing Private Equity in Developed and Emerging Markets</i>

2019· article· en· W2924161261 on OpenAlexaff
Darek Klonowski

Bibliographic record

VenueThe Journal of Private Equity · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsBrandon University
Fundersnot available
KeywordsPrivate equityEquity (law)Emerging marketsPortfolioPrivate equity fundBusinessPrivate equity secondary marketPrivate equity firmEquity capital marketsMarket liquidityClub dealAsset allocationMonetary economicsAsset (computer security)EconomicsFinancial economicsFinance

Abstract

fetched live from OpenAlex

International private equity faces transition issues. In developed markets, it show signs of industry maturation (i.e., lower returns compared with the past, slower rates of growth in the value of fundraising and investing, and ever-increasing accumulation of “dry powder”). In contrast, private equity in emerging markets experiences some evolutionary pressures (i.e., volatile but growing returns, inconsistent growth rates in key statistics, and institutional challenges). This dichotomy creates multiple problems for limited partners and general partners regarding asset allocation, liquidity considerations, and search for premium returns. This article evaluates these issues in detail. TOPICS:Private equity, developed, emerging, equity portfolio management

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0040.006
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.280
Teacher spread0.249 · 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 designObservational
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

Citations3
Published2019
Admission routes1
Has abstractyes

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