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Record W3125924211 · doi:10.1177/0308518x20984484

The geography of business angel investments in the UK: Does local bias (still) matter?

2021· article· en· W3125924211 on OpenAlex
Marc Cowling, Ross Brown, Neil Lee

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

VenueEnvironment and Planning A Economy and Space · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)Quarter (Canadian coin)Face (sociological concept)FinanceEconomicsFinancial marketCapital (architecture)BusinessPolitical scienceSociologyGeography

Abstract

fetched live from OpenAlex

Business angels (BAs) - high net worth individuals who provide informal risk capital to firms - are seen as important providers of entrepreneurial finance. Theory and conventional wisdom suggest that the need for face-to-face interaction will ensure angels will have a strong predilection for local investments. We empirically test this assumption using a large representative survey of UK BAs. Our results show local bias is less common than previously thought with only one quarter of total investments made locally. However, we also show pronounced regional disparities, with investment activity dominated by BAs in London and Southern England. In these locations there is a stronger propensity for localised investment patterns mediated by the ‘thick’ nature of the informal risk capital market. Together these trends further reinforce and exacerbate the disparities evident in the UK’s financial system. The findings make an important contribution to the literature and public policy debates on the uneven nature of financial markets for sources of entrepreneurial finance.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.125
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.185
Teacher spread0.171 · 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