The lost generation of entrepreneurs? The impact of COVID-19 on the availability of risk capital in Canada
Bibliographic record
Abstract
Purpose Canada has lagged in access to capital for high-potential, growth-oriented new ventures, but has made considerable strides in the past decade. This study aims to examine the evolving state of the market for risk capital in Canada during the COVID-19 pandemic, providing a critical assessment of government policy from the perspective of angel investors and diverse communities of entrepreneurs. Design/methodology/approach A thematic analysis was conducted of seven COVID-19 roundtable discussions hosted by the National Angel Capital Organization that included 51 global and national-level business and political leaders. The analysis extracted the most salient details from the discussions, distilling them into timely and actionable insights for policymakers. Findings The analysis suggests that the government’s economic policy response to the COVID-19 crisis fails to address the sudden liquidity problems faced by new ventures. Entrepreneurs and angel investors have remained resilient, rallied as a community and demonstrated an extraordinary level of trust. Traditionally under-represented communities of entrepreneurs are more affected by the crisis than others. Practical implications The findings and recommendations are of relevance to policymakers interested in post-COVID-19 economic policies to address the unique challenges faced by start-ups and ensure their full contribution to economic recovery. Originality/value The paper presents several policy recommendations and proposes a novel framework to describe the impacts of the pandemic on different categories of start-ups.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".