Sustainable Investments in Responsible SMEs: That’s What’s Distinguish Government VCs from Private VCs
Bibliographic record
Abstract
Researchers question the impact of governmental venture capitalists (GVC) compared to private venture capitalists (PVC), but we know little about why this difference occurs and if this criticism is justified. We observed a group of GVCs and developed a new model that describes the way that GVCs process signals pre- and post-decisions. Certain macro level factors severely undermine micro level performance, causing GVCs to financially underperform with respect to PVCs. This helped us to understand that GVCs do not make investment decisions in the same way as PVCs, and what undermines the performance of GVCs’ decision-making processes. The main goals of GVCs are to promote investments in responsible SMEs, mobilizing societal impact. We discuss that the criticism of GVC needs to be more nuanced, as they have a different role than PVC in the financial system as providers of sustainable investments in responsible SMEs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| 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".