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Record W2154478757 · doi:10.1111/jems.12093

Crowdfunding: Geography, Social Networks, and the Timing of Investment Decisions

2015· article· en· W2154478757 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

VenueJournal of Economics & Management Strategy · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSocial connectednessProxy (statistics)The InternetInvestment (military)Equity crowdfundingSocial network (sociolinguistics)BusinessSocial mediaPolitical scienceWorld Wide WebPsychologySocial psychologyFinanceComputer science

Abstract

fetched live from OpenAlex

We examine a crowdfunding platform that connects artists with funders. Although the Internet reduces many distance‐related frictions, local and distant funders exhibit different funding patterns. Local funders appear less responsive to information about the cumulative funds raised by an artist. However, this distance effect appears to proxy for a social effect: it is largely explained by funders who likely have an offline social relationship with the artist (“friends and family”). Yet, this social effect does not persist past the first investment, suggesting that it may be driven by an activity like search but not monitoring. Thus, although the platform seems to diminish many distance‐sensitive costs, it does not eliminate all of them. These findings provide a deeper understanding of the abilities and limitations of online markets to facilitate transactions and convey information between buyers and sellers with varying degrees of social connectedness.

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)0.001
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.060
GPT teacher head0.246
Teacher spread0.186 · 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