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Record W3183287350 · doi:10.1111/1467-8551.12535

Editorial: Entrepreneurial Finance and the Legacy of Mike Wright

2021· editorial· en· W3183287350 on OpenAlexaff
Pawan Budhwar, Douglas J. Cumming, Geoffrey Wood

Bibliographic record

VenueBritish Journal of Management · 2021
Typeeditorial
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsWestern University
Fundersnot available
KeywordsWrightManagementEconomicsSociologyArtArt history

Abstract

fetched live from OpenAlex

This collection of papers was gathered together to celebrate the lifetime scholarly achievements of Mike Wright, Fellow of the British Academy of Management (BAM). Mike was a founder and doyen of the rapidly growing area of entrepreneurial finance, a multidisciplinary area that brings together insights from entrepreneurship, corporate finance, human resource management and strategic management. As such, it is an area of relevance and interest to many in the BAM community. What the field seeks to do is identify and better understand new categories of investors who seek to play a more hands-on role in the management of companies and what they do; the former would include private equity (PE), venture capital (VC) and crowdfunding. The British Journal of Management (BJM) was delighted that so many of the papers submitted involved scholars who were either former collaborators of Mike, or very closely influenced by his work; this represents a lasting testimony to his contribution to the field.

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)0.006
metaresearch head score (Gemma)0.035
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: Editorial
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.035
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.002
Science and technology studies0.0050.003
Scholarly communication0.0090.006
Open science0.0030.002
Research integrity0.0110.015
Insufficient payload (model declined to judge)0.0100.010

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 head0.005
GPT teacher head0.200
Teacher spread0.195 · 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

Citations10
Published2021
Admission routes1
Has abstractyes

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