Social Threat Framing on the Fundraising Performance: Evidence from Equity-based Crowdfunding Firms
Bibliographic record
Abstract
In this study, we seek to investigate the impact of a firm’s social threat framing on its fundraising performance in equity-based crowdfunding. Crowdfunding ventures have growingly committed to social initiatives to attract investors. However, the success crucially depends on how much the investors value the prosocial cues presented in the proposal. Drawing on the perspective of threat framing, we argue that firms’ framing of social issues as a societal threat in their crowdfunding proposals promotes the fundraising performance. A social threat framing increases perceived importance of the firm’s business and sustainability initiatives in the eyes of investors by developing a sense of urgency and commitment towards the social issues. Using a sample of 229 U.S. equity crowdfunding firms from 2015 to 2021, we found a significant positive relationship between social threat framing and the fundraising performance. We also examined some conditional variables for such an effect, such as firm characteristics and the linguistic styles used in the crowdfunding proposals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".