Crowdfunding Amidst FinTech Winter: Complement or Substitute?
Bibliographic record
Abstract
This study examines the transformative potential of FinTech, particularly crowdfunding, in the context of traditional financial systems amidst the FinTech market downturn (‘Winter’) of 2022. We address a fundamental question: Does crowdfunding represent a viable alternative to conventional finance, or does it merely function as an extension of existing financial infrastructure? To investigate this relationship empirically, we developed a proprietary crowdfunding index and employed Interconnectedness Index methodology to compare the spillover effects of crowdfunding and traditional financial systems with common economic factors such as interest rates, USD index, economic uncertainty, cryptocurrency (Bitcoin), as well as commodities (gold and oil). Despite crowdfunding’s remarkable growth trajectory over the past decade, our empirical evidence indicates that it has not yet emerged as a viable substitute for conventional financial mechanisms. These findings carry substantial implications for regulatory frameworks, industry stakeholders, and academic discourse, contributing to the broader understanding of FinTech’s disruptive capacity within the financial ecosystem.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".