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Record W2133263811 · doi:10.3386/w16820

The Geography of Crowdfunding

2011· report· en· W2133263811 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNational Bureau of Economic Research · 2011
Typereport
Languageen
FieldBusiness, Management and Accounting
TopicPrivate Equity and Venture Capital
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGeographical distanceThe InternetBusinessEconomic geographyFinanceEntrepreneurial financeMarketingEconomicsEntrepreneurshipSociologyWorld Wide WebComputer science

Abstract

fetched live from OpenAlex

Perhaps the most striking feature of "crowdfunding" is the broad geographic dispersion of investors in small, early-stage projects. This contrasts with existing theories that predict entrepreneurs and investors will be co-located due to distance-sensitive costs. We examine a crowdfunding setting that connects artist-entrepreneurs with investors over the internet for financing musical projects. The average distance between artists and investors is about 3,000 miles, suggesting a reduced role for spatial proximity. Still, distance does play a role. Within a single round of financing, local investors invest relatively early, and they appear less responsive to decisions by other investors. We show this geography effect is driven by investors who likely have a personal connection with the artist-entrepreneur ("family and friends"). Although the online platform seems to eliminate most distance-related economic frictions such as monitoring progress, providing input, and gathering information, it does not eliminate social-related frictions.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.412
GPT teacher head0.474
Teacher spread0.063 · 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