The Equity Incentive Canadian Startups Need (Hint: It Is Not Stock Options)
Bibliographic record
Abstract
Growth companies contribute disproportionately to Canada’s job creation, economic development and innovation. Most growth companies can match neither the salaries nor the security of more established competitors for executive talent. This makes their only advantage — the growth prospects of their equity — a particularly important part of their compensation arrangements. Canadian growth companies (and Canadian businesses generally) make less use of equity incentives than their American peers and the kind of incentive they use almost exclusively, stock options, are strongly criticized by politicians, academics, institutional shareholders, and corporate governance experts. Stock options are accused of contributing to income inequality and creating incentives for value-destroying behaviour in large established corporations, but it is not clear these critiques have much to do with their use by growth companies. As well, it is not clear why these companies should be restricted to the use of stock options as the only equity incentive scheme available to them without adverse tax effects. For example, there are good reasons American growth companies make extensive use of share grants. As Canada enters its fourth round of amendments in this century to the tax rules relating to equity incentives, it is time to consider a tax regime that begins to differentiate between growth companies and their larger , more established counterparts, and that ceases to differentiate between issuing an option to acquire shares and simply issuing shares.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.028 | 0.003 |
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".