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Record W2116816638

Grassroots Capitalism or: How I Learned to Stop Worrying About Financial Risk in the Exempt Market and Love Equity Crowdfunding

2014· article· en· W2116816638 on OpenAlexvenueaboutno aff
Marco Figliomeni

Bibliographic record

VenueDalhousie journal of legal studies · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsnot available
Fundersnot available
KeywordsEquity crowdfundingSeed moneyGrassrootsProspectusBusinessEquity (law)FinanceEconomicsMarket economyLaw
DOInot available

Abstract

fetched live from OpenAlex

Crowdfunding represents a successful grassroots response to the funding gap present in many independent creative projects. While it traditionally operates on the basis of donations and rewards, the Ontario Securities Commission (OSC) has proposed implementing equity crowdfunding, which would permit the online sale of corporate securities to retail investors. This paper posits that equity crowdfunding should be adopted in Ontario. The ensuing growth in capital markets will ultimately benefit the Canadian economy and, in particular, the entertainment sector. The OSC’s proposed regulatory framework for a crowdfunding prospectus exemption is a step in the right direction. The streamlined process makes it easier and less expensive for early-stage businesses to raise muchneeded capital. The Internet’s global reach serves to match entrepreneurs and prospective investors with unprecedented ease. These reduced barriers create opportunities to kick-start the economy. The anonymity and ubiquity of the Internet make it equally important to provide sufficient investor protection. The OSC’s proposal does this in a number of ways: initial and continuous disclosure, modest investment limits, risk acknowledgement, and regulatory oversight. However, the OSC should also consider implementing a statutory action for continuous disclosure misrepresentation. The investment model of crowdfunding preserves the democratic spirit and accessibility that are essential to this funding mechanism. A case study demonstrates how this model may also benefit large capital-intensive projects in the entertainment industry

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 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)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.001
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 head0.042
GPT teacher head0.296
Teacher spread0.254 · 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 teacher head, not a consensus.

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

Citations2
Published2014
Admission routes2
Has abstractyes

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Same venueDalhousie journal of legal studiesSame topicFinTech, Crowdfunding, Digital FinanceFrench-language works237,207