Not all leavers are equal: How rank and destination influence enforcement of restrictive covenants
Bibliographic record
Abstract
Restrictive covenants like non-competes, non-solicitations, and non-disclosures may pose barriers to spinout ventures and mobility to competitors. However, we know little about the enforceability of these agreements despite their widespread use and associated chilling effects. Examining 332 Canadian court decisions, we find a higher rate of enforcement in cases involving high rank leavers (i.e., managers and owners) versus low rank leavers (regular employees and contractors) especially those who form spinout ventures. Our key insight is that enforcement rates differ significantly across different types of leavers. Low rank leavers and their previous employers may overestimate the potential for enforcement, creating chilling effects (i.e., where employees think they are more restricted by their employment agreements than they really are) that can deter employee mobility and entrepreneurship. • Restrictive covenant enforcement rates differ significantly across types of leavers. • High rank leavers that do spinouts are most vulnerable to enforcement. • Low rank leavers may overestimate restrictive covenant enforcement, leading to chilling effects.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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".