#35 Capital Migration w/ Sean O'Connor of Conexus Venture Capital
Bibliographic record
Abstract
Dan talks with Sean O'Connor, Fund Manager for the Conexus Venture Capital Fund about moving from the major tech hub of Vancouver to prairie Canada to run a brand new fund that invests in their booming tech ecosystem. Conexus Credit Union is just that, a local credit union. In 2019, they did what no other credit union in North America had ever done before and started a venture capital fund to invest in early-stage tech startups. As the tech ecosystem had started booming in Saskatchewan, more capital had started to migrate to the region from Silicon Valley and other major hubs like Toronto. However, Conexus noticed a gap in access to early-stage capital for startups. So they tapped Sean O'Connor, from the Vancouver fintech startup darling Grow Technologies. Sean, like a lot of capital these days, migrated to the prairies to blaze new trails in what's becoming one of Canada's hottest startup markets.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.090 | 0.002 |
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; both teacher heads agree on what is shown here.
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".