Home Country Bias in the Legal System: Empirical Evidence from the Intellectual Property Rights Protection in Canada
Bibliographic record
Abstract
Are judges concerned with the effect of their decisions on national welfare in the same way as policy-makers do? In this paper we analyze this question by examining the outcomes of intellectual property rights (IPR) litigations between domestic and foreign .rms. We develop a simple model of oligopoly where foreign .rms have access to more efficient production technology and show that weak protection of foreign-owned IPR always leads to welfare gains at home. We also show that the positive welfare e¤ect increases with the size of the foreign innovator, as well as in the size of the domestic imitator. We test predictions of the model using the data on all Canadian IPR cases over a four-year period. We find that domestic firms are substantially more likely, by 17 percentage points, to succeed in litigations with foreign firms than with other Canadian firms. We also find evidence supporting the hypothesis of the home bias in the legal system. Specifically, we establish that courts' decisions are aligned with welfare maximization principles so that foreign firms are less likely to win in those cases when the implied welfare gains from not protecting foreign IPR are greater.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".